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  • Statistics In Transition

 

Research Article | 27-December-2017

Extended Kalman Filtering and Pathloss modeling for Shadow Power Parameter Estimation in Mobile Wireless Communications

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, Volume 7 , ISSUE 2, 898–924

Research Article | 13-December-2017

RAILWAY WHEELSET PARAMETER ESTIMATION USING SIGNALS FROM LATERAL VELOCITY SENSOR

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, Volume 1 , ISSUE 3, 754–770

Article | 01-June-2015

RESEARCH ON CAMERA-BASED HUMAN BODY TRACKING USING IMPROVED CAM-SHIFT ALGORITHM

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, Volume 8 , ISSUE 2, 1104–1122

Article | 01-June-2020

Application of iterated filtering to stochastic volatility models based on non-Gaussian Ornstein-Uhlenbeck process

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, Volume 21 , ISSUE 2, 173–187

Article | 06-July-2017

TRANSMUTED KUMARASWAMY DISTRIBUTION

Muhammad Shuaib Khan, Robert King, Irene Lena Hudson

Statistics in Transition New Series, Volume 17 , ISSUE 2, 183–210

Article | 05-September-2021

A new count data model applied in the analysis of vaccine adverse events and insurance claims

The article presents a new probability distribution, created by compounding the Poisson distribution with the weighted exponential distribution. Important mathematical and statistical properties of the distribution have been derived and discussed. The paper describes the proposed model’s parameter estimation, performed by means of the maximum likelihood method. Finally, real data sets are analyzed to verify the suitability of the proposed distribution in modeling count data sets

Showkat Ahmad Dar, Anwar Hassan, Ahmad Para Bilal, Sameer Ahmad Wani

Statistics in Transition New Series, Volume 22 , ISSUE 3, 157–174

Article | 20-September-2020

Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data

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, Volume 21 , ISSUE 3, 171–184

Article | 03-November-2017

SIMULTANEOUS PERIODIC OUTPUT FEEDBACK CONTROL FOR PIEZOELECTRIC ACTUATED STRUCTURES USING INTERVAL METHODS

In this paper, the problem of modeling, output feedback control design and the experimental implementation for the vibration control of smart cantilever beam with parameter uncertainties represented in interval form is addressed. The interval model of the system is obtained by introducing variation in the parameter of the identified model. However, Uncertainties are assumed in the model, identified through on line recursive least square parameter estimation. The control and identification

S. Neduncheliyan, M. Umapathy, D. Ezhilarasi

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 3, 417–431

Research Article | 08-December-2021

A new extension of Odd Half-Cauchy Family of Distributions: properties and applications with regression modeling

The paper proposes a new family of continuous distributions called the extended odd half Cauchy-G. It is based on the T − X construction of Alzaatreh et al. (2013) by consider ing half Cauchy distribution for T and the exponentiated G(x;ξ) as the distribution of X. Several particular cases are outlined and a number of important statistical characteristics of this family are investigated. Parameter estimation via several methods, including maximum likelihood, is discussed and followed

Subrata Chakraburty, Morad Alizadeh, Laba Handique, Emrah Altun, G. G. Hamedani

Statistics in Transition New Series, Volume 22 , ISSUE 4, 77–100

Article | 13-December-2019

LINEAR CHOLESKY DECOMPOSITION OF COVARIANCE MATRICES IN MIXED MODELS WITH CORRELATED RANDOM EFFECTS

, we developed a linear Cholesky decomposition of the random effects covariance matrix, providing a framework for inference that accounts for correlations induced by covariate(s) shared by both fixed and random effects design matrices, a circumstance leading to lack of independence between random errors and random effects. The proposed decomposition is particularly useful in parameter estimation using the maximum likelihood and restricted/residual maximum likelihood procedures.

Anasu Rabe, D. K. Shangodoyin, K. Thaga

Statistics in Transition New Series, Volume 20 , ISSUE 4, 59–70

Article | 06-July-2017

SMALL AREA ESTIMATION OF INCOME UNDER SPATIAL SAR MODEL

and adapts the idea of parameter estimation for small areas by means of the HB method in the case of known model hyperparameters. The illustration of the approach mentioned above was based on a real-world example concerning household income data. The precision of the direct estimators was determined using own three-stage procedure which employs Balanced Repeated Replication, bootstrap and Generalized Variance Function. Additional simulations were conducted to show the influence of the spatial

Jan Kubacki, Alina Jędrzejczak

Statistics in Transition New Series, Volume 17 , ISSUE 3, 365–390

Research Article | 20-February-2013

FEED FORWARD LINEAR QUADRATIC CONTROLLER DESIGN FOR AN INDUSTRIAL ELECTRO HYDRAULIC ACTUATOR SYSTEM WITH SERVO VALVE

Electro-hydraulic servo actuator (EHA) system consists of several dynamic parts which are widely used in motion control application. These dynamic parts need to be controlled to determine direction of the motion. In this research paper, system identification technique is used for system modeling and the model of the system is estimated by using parameter estimation technique. This process started with collection of input and output data from experimental procedure. The data collected is used

J. Micheal, M.F. Rahmat, N. Abdul Wahab, W.K. Lai

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 1, 155–170

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