VOLUME 19 , ISSUE 2 (June 2018) - List of articles

INTERACTION BETWEEN DATA COLLECTION AND ESTIMATION PHASES IN SURVEYS WITH NONRESPONSE

Carl-Erik Särndal/ Imbi Traat/ Kaur Lumiste

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 wher(..)

DOI: 10.21307/stattrans-2018-011

UNIVARIATE SAMPLE SIZE DETERMINATION BY ALTERNATIVE COMPONENTS: ISSUES ON DESIGN EFFICIENCY FOR COMPLEX SAMPLES

Ceylan Talu Yozgatligil/ H. Öztaş Ayhan

Sample size determination for any sample survey can be based on the desired objectives of the survey as well as the level of confidence of the desired estimates for some survey variables, the desired precision of the survey results and the size of the population. In addition to these, the cost of enumeration can also be considered as an important criterion for sample size determination. Recently, some international organizations have been using univariate sample size determination approaches for(..)

DOI: 10.21307/stattrans-2018-012

EFFICIENT ESTIMATORS OF POPULATION MEAN USING AUXILIARY INFORMATION UNDER SIMPLE RANDOM SAMPLING

Mir Subzar/ Showkat Maqbool/ Tariq Ahmad Raja/ Surya Kant Pal/ Prayas Sharma

In the present study we have proposed an improved family of estimators for estimation of population mean using the auxiliary information of median, quartile deviation, Gini’s mean difference, Downton’s Method, Probability Weighted Moments and their linear combinations with correlation coefficient and coefficient of variation. The performance of the proposed family of estimators is analysed by mean square error and bias and compared with the existing estimators in the literature. By this comparis(..)

DOI: 10.21307/stattrans-2018-013

MODIFIED RECURSIVE BAYESIAN ALGORITHM FOR ESTIMATING TIME-VARYING PARAMETERS IN DYNAMIC LINEAR MODELS

O. Olawale Awe/ A. Adedayo Adepoju

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 estimati(..)

DOI: 10.21307/stattrans-2018-014

A GENERALIZED EXPONENTIAL TYPE ESTIMATOR OF POPULATION MEAN IN THE PRESENCE OF NON-RESPONSE

Siraj Muneer/ Javid Shabbir/ Alamgir Khalil

In this article, we propose a class of generalized exponential type estimators to estimate the finite population mean by using two auxiliary variables under non-response in simple random sampling. The proposed estimator under non-response in different situations has been studied and gives minimum mean square error as compared to all other considered estimators. Usual exponential ratio type estimator, exponential product type estimator and many more estimators are also identified from the propose(..)

DOI: 10.21307/stattrans-2018-015

ON MEASURING POLARIZATION FOR ORDINAL DATA: AN APPROACH BASED ON THE DECOMPOSITION OF THE LETI INDEX

Mauro Mussini

This paper deals with the measurement of polarization for ordinal data. Polarization in the distribution of an ordinal variable is measured by using the decomposition of the Leti heterogeneity index. The ratio of the between-group component of the index to the within-group component is used to measure the degree of polarization for an ordinal variable. This polarization measure does not require imposing cardinality on ordered categories to quantify the degree of polarization in the distribution (..)

DOI: 10.21307/stattrans-2018-016

A NEW METHOD FOR COVARIATE SELECTION IN COX MODEL

Ujjwal Das/ Nader Ebrahimi

In a wide spectrum of natural and social sciences, very often one encounters a large number of predictors for time to event data. An important task is to select right ones, and thereafter carry out the analysis. The l1 penalized regression, known as “least absolute shrinkage and selection operator" (LASSO) became a popular approach for predictor selection in last two decades. The LASSO regression involves a penalizing parameter (commonly denoted by l) which controls the extent of penalty and hen(..)

DOI: 10.21307/stattrans-2018-017

COHORT PATTERNS OF FERTILITY IN POLAND BASED ON STAGING PROCESS – GENERATIONS 1930-1980

Wioletta Grzenda/ Ewa Frątczak

As a transition country in the region of Central and Eastern Europe, Poland has experienced unprecedented changes in the fertility. Currently, the total fertility rate level is very low, ca. 1.3 children per woman, which is below the replacement level. Many studies have described changes in fertility based on the crosssectional approach. However, the changes of cohort fertility have been described not quite sufficiently. Our paper complements this gap by the assessment of stochastic fertility ta(..)

DOI: 10.21307/stattrans-2018-018

GENERALIZED EXPONENTIAL SMOOTHING IN PREDICTION OF HIERARCHICAL TIME SERIES

Daniel Kosiorowski/ Dominik Mielczarek/ Jerzy P. Rydlewski/ Małgorzata Snarska

Shang and Hyndman (2017) proposed a grouped functional time series forecasting approach as a combination of individual forecasts obtained using the generalized least squares method. We modify their methodology using a generalized exponential smoothing technique for the most disaggregated functional time series in order to obtain a more robust predictor. We discuss some properties of our proposals based on the results obtained via simulation studies and analysis of real data related to the predic(..)

DOI: 10.21307/stattrans-2018-019

ON A SURPRISING RESULT OF TWO-CANDIDATE ELECTION FORECAST BASED ON THE FIRST LEADERSHIP TIME

Czeslaw Stępniak

This is a simple but provocative note. Consider an election with two candidates and suppose that candidate A was the leader until counting n votes. How to use this information in predicting the final results of the election? According to the common belief the final number of votes for the leader should be a strictly increasing function of n. Assuming the votes are counted in random order we derive the Maximum Likelihood predictor of the final number of votes for the future winner and loser based(..)

DOI: 10.21307/stattrans-2018-020

THE WELLBEING EFFECT OF COMMUNITY DEVELOPMENT. SOME MEASUREMENT AND MODELING ISSUES

Włodzimierz Okrasa/ Dominik Rozkrut

The two interconnected methodological tasks – measurement and modeling – become especially challenging in the context of exploration of the interaction between the local community development and individual wellbeing. In this paper, the preliminary results illustrate usefulness of an analytical framework aimed to assess an impact of the local development on individual wellbeing through multilevel modeling, accounting for spatial effects is. To this aim, a dual measurement system is employed with(..)

DOI: 10.21307/stattrans-2018-021

No Record Found..

Page Actions

Publications

Statistics in Transition New Series

An International Journal of the Polish Statistical Association

FEATURED ARTICLES