Research Article
In order to reduce the location estimation error in Wireless Sensor Network(WSN). A localization algorithm is proposed combining adaptive estimation, PI-learning and spring-relaxation techniques for wireless sensor networks in this paper. Our proposed method takes the advantages of the spring-relaxation technique, thus it inherits its simplicity. The overall accuracy of the location estimations is improved by introducing adaptive estimation and PI-learning. Moreover, it requires only a few
Li Haiyan,
Hu Yun-an,
Zhu Min
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 317–332
Research Communicate
The article contains some theoretical remarks about selected models of position parameters estimation as well as numerical examples of the problem. We ask a question concerning the existence of possible measures of the quality of interval estimation and we mention some popular measures applied to the task. Point estimation is insufficient in practical problems and it is rather interval estimation that is in wide use. Too wide interval suggests that the information available is not sufficient to
Czesław Domański
Statistics in Transition New Series , ISSUE 3, 549–558
Article
The power spectral estimation is an important element in the random signal analysis. The paper will introduce the principles of the classical power spectral estimation and modern power spectral estimation, analyses their characteristics and application in MATLAB simulation. The variance obtained by the classical power spectral estimation is inversely proportional to its resolution, the resolution of the modern spectral estimation are not subject to this restriction, but also the variance
Chunhuan Song
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 884–908
Article
. Next, before discussing general issues of small area estimation (SAE) in official statistics, the author reminds: the methods of sampling surveys, data collection, estimation procedures, and data quality assessment used for official statistics. Statistical information is published in different breakdowns with stable or even decreasing budget while being legally bound to control the response burden. Special attention is paid, from a practitioner point of view, to synthetic development of small area
Jan Kordos
Statistics in Transition New Series , ISSUE 1, 105–132
Article
The paper presents the method of hierarchical Bayes (HB) estimation under small area models with spatially correlated random effects and a spatial structure implied by the Simultaneous Autoregressive (SAR) process. The idea was to improve the spatial EBLUP by incorporating the HB approach into the estimation algorithm. The computation procedure applied in the paper uses the concept of sampling from a posterior distribution under generalized linear mixed models implemented in WinBUGS software
Jan Kubacki,
Alina Jędrzejczak
Statistics in Transition New Series , ISSUE 3, 365–390
Article
estimation methods, which rely on information from outside the subpopulation of interest, which usually increases estimation precision. The main aim of this paper is to show results of estimation of the poverty indicator at a lower level of spatial aggregation than the one used so far, that is at the level of subregions in Poland (NUTS 3) using the small area estimation methodology (SAE), i.e. a model–based technique – the EBLUP estimator based on the Fay–Herriot model. By optimally
Marcin Szymkowiak,
Andrzej Młodak,
Łukasz Wawrowski
Statistics in Transition New Series , ISSUE 4, 609–635
Research Article
This paper presents a novel velocity estimation method for all terrain ground vehicles. The technique is based on a camera that scans the ground and estimates the velocity by using an optical flow algorithm. The method is tested and validated for different types of terrains such as fine sand, coarse sand, gravel as well as a mixture of coarse sand and gravel. Measured velocities from precise encoders are compared with the velocities predicted by the optical flow algorithm, showing promising
Savan Chhaniyara,
Pished Bunnun,
Lakmal D. Seneviratne,
Kaspar Althoefer
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, –
Research Article
In this paper accurate estimation of parameters, higher order state space prediction methods and Extended Kalman filter (EKF) for modeling shadow power in wireless mobile communications are developed. Path-loss parameter estimation models are compared and evaluated. Shadow power estimation methods in wireless cellular communications are very important for use in power control of mobile device and base station. The methods are validated and compared to existing methods, Kalman Filter (KF) with
George P. Pappas,
Mohamed A. Zohdy
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 898–924
Article
The paper presents the comparison of estimation results for spatial and spatiotemporal small area models. The study was carried out for income-related variables drawn from the Polish Household Budget Survey and explanatory variables from the Polish Local Data Bank for the years 2003-2013. The properties of EBLUPs (Empirical Best Linear Unbiased Predictors) based on spatiotemporal models, which utilize spatial correlation between neighbouring areas as well as historical data, were compared and
Alina Jędrzejczak,
Jan Kubacki
Statistics in Transition New Series , ISSUE 4, 113–134
Research Article
A type of parameter estimation technique based on the linear integral filter (LIF) method, the least-absolute error with variable forgetting factor (LAE+VFF) estimation method, is proposed in this paper to estimate the railway wheelset parameters modelled as a time-varying continuous-time (C-T) system. The inputs to the parameter estimator are the control signal and the railway wheelset system output, which is the wheelset’s lateral velocity. The algorithm includes an instrumental variable (IV
H. Selamat,
A. J. Alimin,
Y. M. Sam
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 754–770
Article
In 2011, Germany conducted the first census after the reunification. In contrast to a classical census, a register-assisted census was implemented using population register data and an additional sample. This paper provides an overview of how the sampling design recommendations were set up in order to fulfil legal requirements and to guarantee an optimal but still flexible source of information. The aim was to develop a design that fosters an accurate estimation of the main objective of the
Ralf Münnich,
Jan Pablo Burgard,
Siegfried Gabler,
Matthias Ganninger,
Jan-Philipp Kolb
Statistics in Transition New Series , ISSUE 1, 25–40
Research Article
AUV localization is not accurate based on sequence images if moving target is as landmark,so the moving target detection algorithm is studied based on global motion estimation, which detects and eliminates moving target according to the motion inconsistency of the moving target. Generally grid block matching is used in the global motion estimation, it can’t effectively dispose the dynamic background, and the gradient direction invariant moments descriptors method of free circular neighborhood
GAO Jun-chai,
LIU Ming-yong,
XU Fei
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 360–379
Article
For estimating the missing data of wireless sensor networks, an estimation algorithm called HD method, which can make use of sensoring space-time correlation of the data, was proposed based on mathematical Hermite and DESM statistical models. The algorithm not only can adaptively adjust the time and space weights, but also can accurately estimate the missing or unavailable data. The experimental results show that the algorithm has good stability and relatively high estimation accuracy.
Nan Yan,
Ming-zheng Zhou,
Li Tong
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1032–1053
Article
The growing demand for high-quality statistical data for small areas coming from both the public and private sector makes it necessary to develop appropriate estimation methods. The techniques based on small area models that combine time series and cross-sectional data allow for efficient "borrowing strength" from the entire population and they can also take into account changes over time. In this context, the EBLUP estimation based on multivariate Rao-Yu model, involving both
Alina Jędrzejczak,
Jan Kubacki
Statistics in Transition New Series , ISSUE 4, 725–742
Article
In the article, the problems of objectification of the subjective danger estimation for abnormal cases in air traffic control are considered. An overview of currently existing approaches is given. In addition, the article presents the analysis of the statistical results of testing 252 air traffic controllers. This study reveals a subjective danger estimation inadequacy and its connection to air traffic controller’s potential extreme working capacity. A new approach to objectification of
Olga ARINICHEVA,
Yakov DALINGER,
Aleksei MALISHEVSKII,
Nikolai SUKHIKH,
Yurii KHOROSHAVTSEV
Transport Problems , ISSUE 1, 5–18
Research paper
Small area estimation (SAE) has seen a rapid growth over the past 10 years or so. Earlier work is covered in the author's book (Rao 2003). The main purpose of this paper is to highlight some new developments in model-based SAE since the publication of the author's book. A large part of the new theory addressed practical issues associated with the model-based approach, and we present some of those methods for area level and unit level models. We also briefly mention some new work on synthetic
J. N. K. Rao
Statistics in Transition New Series , ISSUE 4, 491–510
Sampling Methods
The mean squared error reflects only the average prediction accuracy while the distribution of squared prediction error is positively skewed. Hence, assessing or comparing accuracy based on the MSE (which is the mean of squared errors) is insufficient and even inadequate because we should be interested not only in the average but in the whole distribution of prediction errors. This is the reason why we propose to use different than MSE measures of prediction accuracy in small area estimation
Tomasz Żądło
Statistics in Transition New Series , ISSUE 3, 413–432
Research Article
statistics have been derived. Different estimation procedures have also been discussed to estimate the unknown parameters of the proposed probability distribution. The Monte Carlo simulation study has been conducted to compare the performances of the proposed estimators obtained through various methods of estimation. Finally, two real data sets have been used to show the applicability of the proposed model in a real-life scenario.
Abhimanyu Singh Yadav,
S. K. Singh,
Umesh Singh
Statistics in Transition New Series , ISSUE 2, 119–141
Article
The paper presents an empirical study designed to test a small area estimation method. The aim of the study is to apply a robust version of the Fay-Herriot model to the estimation of average wages in the small business sector. Unlike the classical Fay-Herriot model, its robust version makes it possible to meet the assumption of normality of random effects under the presence of outliers. Moreover, the use of this version of the Fay-Herriot model helps to improve the precision of estimates
Grażyna Dehnel,
Łukasz Wawrowski
Statistics in Transition New Series , ISSUE 1, 137–157
Research Article
accidents. Using specific spatial analysis, a model of accident estimation in the urban areas of Bucharest is developed. The study aims to provide useful tools for urban decision makers for a-priori analysis of the consequences of urban outline changes on traffic risks.
Serban RAICU,
Dorinela COSTESCU,
Stefan BURCIU,
Florin RUSCA,
Mircea ROSCA
Transport Problems , ISSUE 3, 33–42
Research paper
In this paper, we first develop a triple-goal small area estimation methodology for simultaneous estimation of unemployment rates for U.S. states using the Current Population Survey (CPS) data and a two-level random sampling variance normal model. The main goal of this paper is to illustrate the utility of the triple-goal methodology in generating a single series of unemployment rate estimates for three separate purposes: developing estimates for individual small area means, producing
Daniel Bonnéry,
Yang Cheng,
Neung Soo Ha,
Partha Lahiri
Statistics in Transition New Series , ISSUE 4, 511–522
Article
To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to
Xinyu Zhang,
Botu Xue,
Guanghu Sui,
Jianjiang Cui
International Journal of Advanced Network, Monitoring and Controls , ISSUE 3, 20–26
Article
In the paper selected nonparametric and semiparametric estimation methods of higher orders quantiles are considered. The construction of nonparametric confidence intervals is based on order statistics of appropriate ranks from random samples or from generated bootstrap samples. Semiparametric bootstrap methods are characterized by double bootstrap simulations. The values of bootstrap sample below the prearranged threshold are generated by the empirical distribution and the values above this
Dorota Pekasiewicz
Statistics in Transition New Series , ISSUE 4, 737–748
Research Article
of unwanted births ends in childbirths, and which are related to deaths and injuries for both mother and child. Due to lack of availability of reliable data at the small level (area-wise) specifically in developing countries like India. In this article the small area estimation technique is used for the estimation of met and unmet need for contraception for 187 towns of Rajasthan state of India and for empirical analysis. Data is taken from the District Level Household Survey (DLHS): 2002-04 and
Piyush Kant Rai,
Sarla Pareek,
Hemlata Joshi
Statistics in Transition New Series , ISSUE 2, 329–360
Article
-validation strategy is proposed to be embedded into the training phase so as to solve the overtraining problem. Experimental results demonstrate that the proposed algorithms are efficient for Facial Age Estimation.
Junhua Ku,
Kongduo Xing
International Journal of Advanced Network, Monitoring and Controls , ISSUE 3, 72–77
Research paper
This paper develops allocation methods for stratified sample surveys in which small area estimation is a priority. We assume stratified sampling with small areas as the strata. Similar to Longford (2006), we seek efficient allocation that minimizes a linear combination of the mean squared errors of composite small area estimators and of an estimator of the overall mean. Unlike Longford, we define mean-squared error in a model-assisted framework, allowing a more natural interpretation of results
W. B. Molefe,
D. K. Shangodoyin,
R. G. Clark
Statistics in Transition New Series , ISSUE 2, 163–182
research-article
The conventional state estimation (SE) is formulated as an iterative weighted least-squares (WLS) problem (Monticelli, 2000; Chakrabarti et al., 2010; Biswal et al., 2012). The WLS SE is a nonlinear regression operation that deduces the response (state variables) from the observation set (measurement set) (Liu et al., 2014). The meters that are associated with the power system SE includes synchronized phasor measurement units (PMUs) and SCADA meters. The SCADA meters which are the conventional
Hatim G. Abood,
Victor Sreeram,
Yateendra Mishra
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 1–12
research-article
Nomenclatures
SE
state estimation
PS
power system
PSN
power system networks
PSO–NN
particle swarm optimization–neural network
DPN
distribution power network
RDPSNs
radial distribution power system networks
DMS
distribution management system
GTP
graph theoretic procedure algorithm
DSSE
distribution system state estimation model
WLS
weighted least square
WLAV
weighted least absolute value
PMUs
phasor measurement units
ANN
artificial neural network
Husham Idan Hussein,
Ghassan Abdullah Salman,
Ahmed Majeed Ghadban
International Journal on Smart Sensing and Intelligent Systems
, ISSUE 1, 1–10
Article
This work is designed to assess the effect of non-response in estimation of the current population mean in two-phase successive sampling on two occasions. Sub-sampling technique of non-respondents has been used and exponential methods of estimation under two-phase successive sampling arrangement have been proposed. Properties of the proposed estimation procedures have been examined. Empirical studies are carried out to justify the suggested estimation procedures and suitable recommendations
G. N. Singh,
M. Khetan,
S. Maurya
Statistics in Transition New Series , ISSUE 2, 163–182
Research paper
The increasing interest in applying small area estimation methods urges the needs for training in small area estimation. To better understand the behaviour of small area estimators in practice, simulations are a feasible way for evaluating and teaching properties of the estimators of interest. By designing such simulation studies, students gain a deeper understanding of small area estimation methods. Thus, we encourage to use appropriate simulations as an additional interactive tool in teaching
Jan Pablo Burgard,
Ralf Münnich
Statistics in Transition New Series , ISSUE 4, 603–610
Article
Recent years have seen a dynamic development in statistical methods for analysing data contaminated with outliers. One of the more important techniques that can deal with outlying observations is robust regression, which represents four decades of research. Until recently the implementation of robust regression methods, such as M-estimation or MM-estimation, was limited owing to their iterative nature. With advances in computing power and the growing availability of statistical packages, such
Grażyna Dehnel
Statistics in Transition New Series , ISSUE 4, 749–762
Research paper
The aim of the paper is to present some experiences in teaching Small Area Estimation (SAE). SAE education experiences and challenges are analysed from the academic side and from the NSI side. An attempt was undertaken to discuss SAE issues in a wider perspective of teaching statistics. In particular, the topics refer to Polish conditions, but they are presented against the background of selected international experiences and practices. Information comes from a special inquiry - a survey
Elżbieta Gołata
Statistics in Transition New Series , ISSUE 4, 611–630
Article
We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes
María Guadarrama,
Isabel Molina,
J. N. K. Rao
Statistics in Transition New Series , ISSUE 1, 41–66
Article
In the paper methods of reducing the so-called boundary effects, which appear in the estimation of certain functional characteristics of a random variable with bounded support, are discussed. The methods of the cumulative distribution function estimation, in particular the kernel method, as well as the phenomenon of increased bias estimation in boundary region are presented. Using simulation methods, the properties of the modified kernel estimator of the distribution function are investigated
Aleksandra Baszczyńska
Statistics in Transition New Series , ISSUE 3, 541–556
Sampling Methods
Inference in surveys with nonresponse has been studied extensively in the literature with a focus on the estimation phase. Propensity weighting and calibrated weighting are among the adjustment methods used to reduce the nonresponse bias. The data collection phase has come into focus more recently; the literature on adaptive survey design emphasizes representativeness and degree of balance as desirable properties of the response obtained from a probability sample. We take an integrated view
Carl-Erik Särndal,
Imbi Traat,
Kaur Lumiste
Statistics in Transition New Series , ISSUE 2, 183–200
Research paper
Stemming from assumption that Gross Domestic Product is an index oversimplifying economic development and not reflecting socio-economic development, the paper presents conceptualization, operationalization and estimation of Balanced Development Index (BDI), concerning both economic and social development in Poland. Actual values of this index as well as its four composite components (middle-level indexes) are presented for 1999-2013. A statistical model allowing estimation of BDI values as well
Andrzej K. Koźmiński,
Adam Noga,
Katarzyna Piotrowska,
Krzysztof Zagórski
Statistics in Transition New Series , ISSUE 3, 461–487
Article
Estimation of the population mean in a finite and fixed population on the basis of the conditional simple random sampling design dependent on order statistics (quantiles) of an auxiliary variable is considered. Properties of the well-known Horvitz-Thompson and ratio type estimators as well as the sample mean are taken into account under the conditional simple random sampling designs. The considered examples of empirical analysis lead to the conclusion that under some additional conditions the
Janusz Wywiał
Statistics in Transition New Series , ISSUE 3, 411–428
Article
The paper is an attempt to trace some of the early developments of small area estimation. The basic papers such as the ones by Fay and Herriott (1979) and Battese, Harter and Fuller (1988) and their follow-ups are discussed in some details. Some of the current topics are also discussed.
Malay Ghosh
Statistics in Transition New Series , ISSUE 4, 1–22
Article
In this paper, a unified and probabilistic method is proposed for simultaneously localization of a mobile service robot and states estimation of surrounding objects and co-existing people. This method allows intelligent robots to navigate reliably in dynamic environments and provide home-care services based on joint localization results. The algorithm makes use of probabilistic model to represent non-static people and objects states. Moreover, Rao-Blackwellized particle filters (RBPFs) are
Kun Qian,
Xudong Ma,
Xian Zhong Dai,
Fang Fang,
Bo Zhou
International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 1081–1096
Article
Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of
VESNA ZUPUNSKI,
RADIVOJE JEVTIC,
VESNA SPASIC JOKIC,
LJUBICA ZUPUNSKI,
MIRJANA LALOSEVIC,
MIHAJLO CIRIC,
ZIVKO CURCIC
Journal of Nematology , ISSUE 2, 150–155
Article
This paper introduces a new generalization of the Pareto distribution using the MarshallOlkin generator and the method of alpha power transformation. This new model has several desirable properties appropriate for modelling right skewed data. The Authors demonstrate how the hazard rate function and moments are obtained. Moreover, an estimation for the new model parameters is provided, through the application of the maximum likelihood and maximum product spacings methods, as well as the Bayesian
Ehab M. Almetwally,
Hanan A. Haj Ahmad
Statistics in Transition New Series , ISSUE 5, 61–84
Research paper
estimation variable and the auxiliary variables employed in the calibration. The JCE achieves better performance when the auxiliary variables can fully explain the variability in the study variables or at least when the auxiliary variables are strong correlates of the estimation variables. As opposed to the standard dual frame estimators, the JCE does not require domain membership information. Even if included in the JCE auxiliary variables, the effect of the randomly misclassified domains does not
Mahmoud A. Elkasabi,
Steven G. Heeringa,
James M. Lepkowski
Statistics in Transition New Series , ISSUE 1, 7–36
Sampling Methods
Estimation in Dynamic Linear Models (DLMs) with Fixed Parameters (FPs) has been faced with considerable limitations due to its inability to capture the dynamics of most time-varying phenomena in econometric studies. An attempt to address this limitation resulted in the use of Recursive Bayesian Algorithms (RBAs) which is also affected by increased computational problems in estimating the Evolution Variance (EV) of the time-varying parameters. In this paper, we propose a modified RBA for
O. Olawale Awe,
A. Adedayo Adepoju
Statistics in Transition New Series , ISSUE 2, 239–258
Research Article
Estimating the current stage of grape ripeness is a crucial step in wine making and becomes especially important during harvesting. Visual inspection of grape seeds is one method to achieve this goal without performing chemical analysis, however this method is prone to failure. In this paper, we propose an unsupervised visual inspection system for grape ripeness estimation using the Dirichlet Mixture Model (DMM). Experimental analysis using real world data demonstrates that our approach can be
S. Hernández,
L. Morales,
A. Urrutia
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 594–612
Article
The paper analyzes the possibility of using the energy signature method based on the linear regression to determine the seasonal energy demand for cooling and ventilation in the office building. The “extended” energy signature method (H-m method) was described and applied. In accordance with Standard (EN 15603) the estimation of energy consumption for cooling can be performed for a period shorter than the entire season, but data range must be appropriate to obtain the correct accuracy of the
Dorota BARTOSZ,
Aleksandra SPECJAŁ
Architecture, Civil Engineering, Environment , ISSUE 2, 133–143
Article
Based on one parameter exponential record data, we conduct statistical inferences (maximum likelihood estimator and Bayesian estimator) for the suggested model parameter. Our second aim is to predict the future (unobserved) records and to construct their corresponding prediction intervals based on observed set of records. In the estimation and prediction processes, we consider the square error loss and the Kullback-Leibler loss functions. Numerical simulations were conducted to evaluate the
Raed r. . Abu Awwad
Statistics in Transition New Series , ISSUE 2, 1–14
Research Communicate
Dominik Sieradzki,
Wojciech Zieliński
Statistics in Transition New Series , ISSUE 3, 541–548
Research Article
This paper proposes a new family of continuous distributions with one extra shape parameter called the generalized Zeghdoudi distributions (GZD). We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. Various statistical properties like stochastic ordering, moment method, maximum likelihood estimation, entropies and limiting distribution of extreme order statistics are established. We prove the flexibility of
Lahsen Bouchahed,
Halim Zeghdoudi
Statistics in Transition New Series , ISSUE 1, 61–74
Research Article
is proposed which enhances the accuracy of speed estimation. It is envisaged that with increasing estimation accuracy, the application of multi-sensor fusion in autonomous vehicles will be greatly enhanced.
Arijit Chowdhury,
Tapas Chakravarty,
P. Balamuralidhar
International Journal on Smart Sensing and Intelligent Systems , ISSUE 5, 1–6
Research Article
Dmytro KOZACHENKO,
Roman VERNIGORA,
Volodymyr BALANOV,
Nazar SANNYTSKYY,
Nikolay BEREZOVY,
Tetiana BOLVANOVSKA
Transport Problems , ISSUE 3, 91–101
Article
In this paper, we proposed an efficient family of ratio-type estimators using one auxiliary variable for the estimation of the current population mean under successive sampling scheme. This family of estimators have been studied by Ray and Sahai (1980) under simple random sampling using one auxiliary variable for estimation of the population mean. Using these estimators in successive sampling, the expression for bias and mean squared error of the proposed estimators are obtained up to the first
Nazeema T. Beevi,
C. Chandran
Statistics in Transition New Series , ISSUE 2, 227–245
Article
The present paper deals with a new median based ratio estimator for the estimation of finite population means in the absence of an auxiliary variable. The bias and mean squared error of the proposed median based ratio estimator are obtained. The performance of the median based ratio estimator is compared with that of the SRSWOR sample mean, ratio estimator and linear regression estimator for certain natural population. It is shown from the numerical comparisons that the proposed median based
J. Subramani
Statistics in Transition New Series , ISSUE 4, 591–604
Research Article
appliances. The function uses Ward's method which is an unsupervised learning for estimation of a user's behavior. In this paper, we evaluated a result of estimate of a user's behavior from sensor data by Ward's method.
Sho Kimura,
Toshihiko Sasama,
Takao Kawamura,
Kazunori Sugahara
International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 920–934
Article
light sources and to select an estimation model of the CRI and the CCT using a low cost RGB sensor. The model estimation has been developed in this work and a separated algorithm for each source type has been built. The results show that using a K-Nearest Neighbor classifier, the error resulted less than $3.6%$. The error of the model estimation for the LED was 1.8%, for fluorescent light sources 0.09% and 1.2% for incandescent light sources.
J.-S. Botero V.,
F.-E. López G.,
J.-F. Vargas B.
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1505–1524
Research paper
Forough Karlberg
Statistics in Transition New Series , ISSUE 4, 541–562
Article
Salah H.R. Ali,
M.A.H. Khalafalla,
Ihab H. Naeim,
Sarwat Z.A. Zahwi
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 397–418
Article
This paper details about the noninvasive estimation of Urea concentration in blood using near infrared spectroscopy (NIRS) and Artificial neural network based prediction model. The absorption spectrum of the urea has been studied experimentally in order to choose the wavelengths of peak absorption. For this purpose, IR absorption spectrum of 0.1M aqueous urea solution has been collected and analyzed in second overtone region of the near-infra red spectra using the Bruker tensor 27 FTIR
Swathi Ramasahayam,
Shubhajit Roy Chowdhury
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 449–467
Article
One of the basic variables used in the process of tariff calculation of premiums in motor liability insurance is the age of the insured. In this type of insurance offered by insurers operating on the Polish market, this variable is taken into account in the ratemaking by discounts and increases in assigned premium, known as the net premiums rates. The aim of this work is to propose a method of rate estimation of net premiums in the groups of the motor third liability insurance portfolio of
Anna Szymańska
Statistics in Transition New Series , ISSUE 1, 151–165
Article
In this study, we introduce a new model called the Extended Exponentiated Power Lindley distribution which extends the Lindley distribution and has increasing, bathtub and upside down shapes for the hazard rate function. It also includes the power Lindley distribution as a special case. Several statistical properties of the distribution are explored, such as the density, hazard rate, survival, quantile functions, and moments. Estimation using the maximum likelihood method and inference on a
V. Ranjbar,
M. Alizadeh,
G. G. Hademani
Statistics in Transition New Series , ISSUE 4, 621–643
Article
A new distribution called Generalized Odd Fréchet (GOF) distribution is presented and its properties explored. Some structural properties of the proposed distribution, including the shapes of the hazard rate function, moments, conditional moments, moment generating function, skewness, and kurtosis are presented. Mean deviations, Lorenz and Bonferroni curves, Rényi entropy, and the distribution of order statistics are given. The maximum likelihood estimation technique is used to
Shahdie Marganpoor,
Vahid Ranjbar,
Morad Alizadeh,
Kamel Abdollahnezhad
Statistics in Transition New Series , ISSUE 3, 109–128
Article
can be detected. Then, with the analysis of particle filtering and traditional Cam-shift algorithm, we introduce a new human body tracking method that is able to choose the target automatically due to the detection result. On the basis of the detection and tracking results, the algorithm of motion parameter estimation is analyzed. Finally, a set of human body detection and tracking experiments are designed to demonstrate the effectiveness of the proposed algorithms.
Jiude Li
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 1104–1122
Article
seismograms are calculated through the fast algorithm, and the multi-path parameters as well as the difference of travel time between a reference position and the seismographic stations are given by an optimization algorithm in the frequency domain. The new approach can work under conditions of refraction interference, and improve the estimation performance by using an extended semblance function. Its effectiveness is demonstrated through some numerical examples, and it is shown that the proposed
Lianming Sun
International Journal of Advanced Network, Monitoring and Controls , ISSUE 1, –
Research Article
A study on two-parameter power Ishita distribution (PID), of which Ishita distribution introduced by Shanker and Shukla (2017 a) is a special case, has been carried out and its important statistical properties including shapes of the density, moments, skewness and kurtosis measures, hazard rate function, and stochastic ordering have been discussed. The maximum likelihood estimation has been discussed for estimating its parameters. An application of the distribution has been explained with a
Kamlesh Kumar Shukla,
Rama Shanker
Statistics in Transition New Series , ISSUE 1, 135–148
Research paper
If the implementation of small area estimation methods to multiple editions of a repeated sample survey is considered, then the question arises which covariates to use in the models. Applying standard model selection procedures independently to the different editions of the survey may identify different sets of covariates for each edition. If the small area predictions are sensitive to the different models, this is undesirable in official statistics since monitoring change over time of
Jan A. van den Brakel,
Bart Buelens
Statistics in Transition New Series , ISSUE 4, 523–540
Research Article
Different approaches of non-destructive estimation of the LAI in winter wheat were compared. Plant height had weak relation with the LAI, while estimated biomass showed high logarithmic relationship (R2=0.839). NDRE and REIP were logarithmically well related to the LAI (R2=0.726 and 0.779 respectively). Saturation effect of NDRE and REIP was less than NDVI. Some RGB-based indices also showed good potential to estimate the LAI. Among the indices, Gm, GMB, RMB, and NRMB were better related to the
H. Tavakoli,
S.S. Mohtasebi,
R. Alimardani,
R. Gebbers
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 337–359
Article
Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of
Amitava Akuli,
Abhra Pal,
Gopinath Bej,
Tamal Dey,
Arunangshu Ghosh,
Bipan Tudu,
Nabarun Bhattacharyya,
Rajib Bandyopadhyay
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 709–731
Article
In this paper, we estimate the eye gaze by using the face direction to estimate the object of interest in an extensive area such as an educational display or museum exhibit. However, the direction of the gaze may differ from that of the face. Therefore, our approach was to use a method that utilizes both the face and eye directions to improve the accuracy of our estimation compared to only using the face direction. The first part of our study involved apprehending the relationship between the
Haruya Tamaki,
Tsugunosuke Sakai,
Yosuke Ota,
Fusako Kusunoki,
Shigenori Inagaki,
Ryohei Egusa,
Masanori Sugimoto,
Hiroshi Mizoguchi
International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, –
Article
Chetan Sharma,
Sachin Kumar,
Anshul Bhargava,
Shubhajit Roy Chowdhury
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1267–1282
Article
In this paper, an investigation has been carried out to deal with a unified approach of estimation procedures of population variance in two-phase sampling design under missing at random non-response mechanism circumstances. Using two auxiliary variables, we have developed different chain-type exponential estimators of finite population variance for two different set-ups and studied their properties under the different assumption of random non-response considered by Tracy and Osahan (1994). The
G. N. Singh,
Amod Kumar,
Gajendra K. Vishwakarma
Statistics in Transition New Series , ISSUE 4, 575–596
Research paper
We show on an application to small-area statistics that efficient estimation is not always conducive to good policy decisions because the established inferential procedures have no capacity to incorporate the priorities and preferences of the policy makers and the related consequences of incorrect decisions. A method that addresses these deficiencies is described. We argue that elicitation of the perspectives of the client (sponsor) and their quantification are essential elements of the
Nicholas T. Longford
Statistics in Transition New Series , ISSUE 1, 65–82
Research Article
This article focuses on the synthesis of conditional dependence structure of recursive Bayesian estimation of dynamic state space models with time-varying parameters using a newly modified recursive Bayesian algorithm. The results of empirical applications to climate data from Nigeria reveals that the relationship between energy consumption and carbon dioxide emission in Nigeria reached the lowest peak in the late 1980s and the highest peak in early 2000. For South Africa, the slope trajectory
Olushina Olawale Awe,
Abosede Adedayo Adepoju
Statistics in Transition New Series , ISSUE 1, 123–136
Article
, within spatio temporal domains subdivided by the mode of fishing. Because many of these domains have small sample sizes, small area estimation methods are developed. Bayesian inference for the circular distributions on the 24-hour clock is conducted, based on a large set of observed daily departure times from another National Marine Fisheries Service study, the Coastal Household Telephone Survey. A novel variational/Laplace approximation to the posterior distribution allows fast comparison of a large
Daniel Hernandez-Stumpfhauser,
F. Jay Breidt,
Jean D. Opsomer
Statistics in Transition New Series , ISSUE 1, 91–104
Research paper
Linear area level models for small area estimation, such as the Fay-Herriot model, face challenges when applied to discrete survey data. Such data commonly arise as direct survey estimates of the number of persons possessing some characteristic, such as the number of persons in poverty. For such applications, we examine a binomial/logit normal (BLN) model that assumes a binomial distribution for rescaled survey estimates and a normal distribution with a linear regression mean function for
Carolina Franco,
William R. Bell
Statistics in Transition New Series , ISSUE 4, 563–584
Article
, stochastic ordering, mean deviations, Bonferroni and Lorenz curves, and stress-strength reliability have been discussed. Estimation of its parameter has been discussed using the method of maximum likelihood and the method of moments. The applications and goodness of fit of the distribution have been discussed with three real lifetime data sets and the fit has been compared with one-parameter lifetime distributions including Akash, Shanker, Lindley and exponential distributions.
Rama Shanker
Statistics in Transition New Series , ISSUE 3, 391–410
Research Article
of dispersion have been derived and discussed. The reliability properties, including hazard rate function and mean residual life function, have been discussed. The estimation of its parameters has been discussed using the maximum likelihood method and the applications of the distribution have been explained through some survival time data of a group of patients suffering from head and neck cancer, and the fit has been compared with a one-parameter Lindley distribution and a two-parameter weighted
Rama Shanker,
Kamlesh Kumar Shukla,
Amarendra Mishra
Statistics in Transition New Series , ISSUE 2, 291–310
Article
Y. S. Ramakrishnaiah,
Manish Trivedi,
Konda Satish
Statistics in Transition New Series , ISSUE 1, 87–102
Article
In this paper, the two-parameter Akash distribution is generalized to size-biased twoparameter Akash distribution (SBTPAD). A further modification to SBTPAD is introduced, creating the power size-biased two-parameter Akash distribution (PSBTPAD). Several statistical properties of PSBTPAD distribution are proved. These properties include the following: moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis, the maximum likelihood estimation of the distribution
Khaldoon Alhyasat,
Ibrahim Kamarulzaman,
Amer Ibrahim Al-Omari,
Mohd Aftar Abu Bakar
Statistics in Transition New Series , ISSUE 3, 73–91
Article
Levenberg-Marquardt(abbr. L-M) method based iterative square root cubature Kalman filter (ISRCKFLM) is proposed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation error and nonlinearity of measurement equation. The measurement update of square root cubature Kalman filter (SRCKF) is transformed to the problem of nonlinear least square error, then we use L-M method to solve it and obtain the optimal state estimation and covariance, so the
Jing Mu,
Changyuan Wang
International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 98–106
Article
Levenberg-Marquardt (abbr.L-M) method based iterative square root cubature Kalman filter (abbr. ISRCKFLM) inherits the numerical stability of square root Cubature Kalman filter and effectively suppresses the influence of the larger initial estimation error and the nonlinearity of the measurement equation on the state estimation in the nonlinear state estimation due to obtaining the optimal state and variance estimates using the latest measurement through L-M method. We apply the ISRCKFLM
Mu Jing,
Wang Changyuan
International Journal of Advanced Network, Monitoring and Controls , ISSUE 2, 10–13
Article
their suitability over other modeling methods for the task of perception modeling, taking into account development and implementation complexity. It will be shown that while known points on the perception scales of loudness and pitch can be used to objectively test the suitability of artificial neural networks, it is in the estimation of the perception of sound from the unknown (or unseen) data points that this method excels.
D. Riordan,
P. Doody,
J. Walsh
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 1806–1836
Research paper
There are many sample surveys of populations that contain outliers (extreme values). This is especially true in business, agricultural, household and medicine surveys. Outliers can have a large distorting influence on classical statistical methods that are optimal under the assumption of normality or linearity. As a result, the presence of extreme observations may adversely affect estimation, especially when it is carried out at a low level of aggregation. To deal with this problem, several
Grażyna Dehnel
Statistics in Transition New Series , ISSUE 1, 137–152
Research Article
efficient data communication. During this scheme, if node attains a channel it must wait for a network reconfiguration time for moving to next channel. Hence, during this time other nodes are allowed for moving to the new channel. Secondly, for moving to the new channel load aware channel estimation is proposed to assess the possibility of traffic weight assignment at each channel. Finally, the Particle swarm optimization (PSO) based collision avoiding multiple-channel based superframe scheduling is
Vikram K,
Sarat Kumar Sahoo
International Journal on Smart Sensing and Intelligent Systems , ISSUE 4, 879–902
Research Article
Using the estimation method of ordinary least squares leads to unreliable results in the case of heteroskedastic linear regression model. Other estimation methods are described, including weighted least squares, division of the sample and heteroskedasticity-consistent covariance matrix estimators, all of which can give estimators with better properties than ordinary least squares. The methods are presented giving the example of modelling quality of life of older people, based on a data set from
Katarzyna Jabłońska
Statistics in Transition New Series , ISSUE 3, 423–452
Article
Muhammad Shuaib Khan,
Robert King,
Irene Lena Hudson
Statistics in Transition New Series , ISSUE 2, 183–210
Article
important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance
Aylin Alkaya,
H. Öztaş Ayhan,
Alptekin Esin
Statistics in Transition New Series , ISSUE 2, 247–270
Research Article
Advanced methods of data processing in magnetic anomaly detection (MAD) systems are investigated. Raw signals of MAD based on component magnetic sensors are transformed into energy signals in the space of specially constructed orthonormalized functions. This procedure provides a considerable improvement of the SNR thus enabling reliable target detection. Estimation of the target parameters is implemented with the help of Genetic Algorithm. Numerous computer simulations show good algorithm
B. Ginzburg,
L. Frumkis,
B.Z. Kaplan,
A. Sheinker,
N. Salomonski
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 110–122
Article
In this paper, we consider the problem of estimation of population mean of a study variable by making use of first-phase sample mean and first-phase sample median of the auxiliary variable at the estimation stage. The proposed new estimator of the population mean is compared to the sample mean estimator, ratio estimator and the difference type estimator for the fixed cost of the survey by using the concept of two-phase sampling. The magnitude of the relative efficiency of the proposed new
Kalyan Rao Vadlamudi,
Stephen A. Sedory,
Sarjinder Singh
Statistics in Transition New Series , ISSUE 4, 637–650
Article
A new over-dispersed discrete probability model is introduced, by compounding the Poisson distribution with the weighted Ishita distribution. The statistical properties of the newly introduced distribution have been derived and discussed. Parameter estimation has been done with the application of the maximum likelihood method of estimation, followed by the Monte Carlo simulation procedure to examine the suitability of the ML estimators. In order to verify the applicability of the proposed
Bilal Ahmad Para,
Tariq Rashid Jan
Statistics in Transition New Series , ISSUE 3, 171–184
Article
Barndorff-Nielsen and Shephard (2001) proposed a class of stochastic volatility models in which the volatility follows the Ornstein–Uhlenbeck process driven by a positive Levy process without the Gaussian component. The parameter estimation of these models is challenging because the likelihood function is not available in a closed-form expression. A large number of estimation techniques have been proposed, mainly based on Bayesian inference. The main aim of the paper is to present an
Piotr Szczepocki
Statistics in Transition New Series , ISSUE 2, 173–187
Article
Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A
Andreea L. Erciulescu,
Wayne A. Fuller
Statistics in Transition New Series , ISSUE 1, 9–24
Article
This paper addresses the problem of estimation of population mean of sensitive character using non-sensitive auxiliary variable at current wave in two wave successive sampling. A general class of estimator is proposed and studied under randomized and scrambled response model. Many existing estimators have been modified to work for sensitive population mean estimation. The modified estimators became the members of proposed general class of estimators. The detail properties of all the estimators
Kumari Priyanka,
Pidugu Trisandhya
Statistics in Transition New Series , ISSUE 1, 41–65
Article
In this paper, Self Tuning Fuzzy PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from an
Zulfatman,
M. F. Rahmat
International Journal on Smart Sensing and Intelligent Systems , ISSUE 2, 246–261
Article
The most dominant problem in the survey sampling is to obtain the better ratio estimators for the estimation of population mean or population variance. Estimation theory is enhanced by using the auxiliary information in order to improve on designs, precision and efficiency of estimators. A modified class of ratio estimator is suggested in this paper to estimate the population mean. Expressions for the bias and the mean square error of the proposed estimators are obtained. Both analytical and
Mir Subzar,
S. Maqbool,
T. A. Raja,
Prayas Sharma
Statistics in Transition New Series , ISSUE 4, 181–189
Article
Anoop Chaturvedi,
Sandeep Mishra
Statistics in Transition New Series , ISSUE 2, 15–31
Article
and few feature points.
Aiming at the problems of the above-mentioned visual SLAM system, this paper proposes an algorithm that fuses IMU and SLAM. Through the fusion of IMU, it can provide a good initial pose for the system. At the same time, during the camera movement process, it makes up for the shortcomings of visual SLAM, ensuring the accuracy of the camera pose estimation in the case of fast camera movement and lack of environmental texture.
II.
RELATED WORKS
A.
Camera coordinate system
Yu Haige,
Yu Fan,
Wei Yanxi
International Journal of Advanced Network, Monitoring and Controls , ISSUE 4, 47–55
Article
For the last several decades, the US Census Bureau has been applying AK composite estimation method for estimating monthly levels and month-to-month changes in unemployment using data from the Current Population Survey (CPS), which uses a rotating panel design. For each rotation group, survey-weighted totals, known as monthin-sample estimates, are derived each month to estimate population totals. Denoting the vector of month-in-sample estimates by Y and the design-based variance-covariance
Daniel Bonnéry,
Yang Cheng,
Partha Lahiri
Statistics in Transition New Series , ISSUE 4, 166–190
Research Article
H. S. Su,
Y. Q. Kang
International Journal on Smart Sensing and Intelligent Systems , ISSUE 3, 967–1003
Sampling Methods
RANJITA PANDEY,
KALPANA YADAV
Statistics in Transition New Series , ISSUE 3, 375–392
Article
In this study, a new adaptive sliding-mode observer is proposed to estimate the rotor position and speed for sensorless control of permanent-magnet synchronous motor (PMSM) in an electric vehicle drive system. This observer can effectively reduce the estimation errors caused by the inherent chattering phenomenon for a conventional sliding-mode observer and the stator resistance uncertainty due to the variation of motor temperature. This new sliding-mode observer is designed by using a
Xiong Xiao,
Yongjun Zhang,
Jing Wang,
Haiping Du
International Journal on Smart Sensing and Intelligent Systems , ISSUE 1, 377–396
Article
Small domain estimation covers a set of statistical methods for estimating quantities in domains not previously considered by the sample design. In such cases, the use of a model-based approach that relates sample estimates to auxiliary variables is indicated. In this paper, we propose and evaluate skew normal small area time models for the Brazilian Annual Service Sector Survey (BASSS), carried out by the Brazilian Institute of Geography and Statistics (IBGE). The BASSS sampling plan cannot
André Felipe Azevedo Neves,
Denise Britz do Nascimento Silva,
Fernando Antônio da Silva Moura
Statistics in Transition New Series , ISSUE 4, 84–102