Publications

Share / Export Citation / Email / Print / Text size:

Statistics in Transition New Series

An International Journal of the Polish Statistical Association

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics , Statistics & Probability

GET ALERTS

ISSN: 1234-7655
eISSN: 2450-0291

DESCRIPTION

FEATURED ARTICLES

SUBJECTIVE AND COMMUNITY WELL-BEING INTERACTION IN A MULTILEVEL SPATIAL  MODELLING FRAMEWORK
LINEAR CHOLESKY DECOMPOSITION OF COVARIANCE MATRICES IN MIXED MODELS WITH CORRELATED RANDOM EFFECTS

VOLUME 21 , ISSUE 4 (August 2020) - List of articles

Special Issue

Small area estimation: its evolution in five decades

Malay Ghosh

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.

DOI: 10.21307/stattrans-2020-022

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

Julie Gershunskaya

DOI: 10.21307/stattrans-2020-023

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

Ying Han

DOI: 10.21307/stattrans-2020-024

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

Yan Li

DOI: 10.2137/stattrans-2020-025

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

Isabel Molina

DOI: 10.21307/stattrans-2020-026

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

David Newhouse

DOI: 10.21307/stattrans-2020-027

Published Online: 15-September-2020

Discussion of “Small area estimation: its evolution in five decades”, by Malay Ghosh

Danny Pfeffermann

DOI: 10.2137/stattrans-2020-028

Published Online: 15-September-2020

Discussion of “Small Area Estimation: Its Evolution in Five Decades”, by Malay Ghosh

J. N. K. Rao

DOI: 10.2137/stattrans-2020-029

Published Online: 15-September-2020

Rejoinder

Malay Ghosh

DOI: 10.21307/stattrans-2020-030

Published Online: 15-September-2020

Effective transformation-based variable selection under two-fold subarea models in small area estimation

Song Cai/ J. N. K. Rao/ Laura Dumitrescu/ Golshid Chatrchi

We present a simple yet effective variable selection method for the two-fold nested subarea model, which generalizes the widely-used Fay-Herriot area model. The twofold subarea model consists of a sampling model and a linking model, which has a nested-error model structure but with unobserved responses. To select variables under the two-fold subarea model, we first transform the linking model into a model with the structure of a regular regression model and unobserved responses. We then estimate(..)

DOI: 10.21307/stattrans-2020-031

Published Online: 15-September-2020

Skew normal small area time models for the Brazilian annual service sector survey

André Felipe Azevedo Neves/ Denise Britz do Nascimento Silva/ Fernando Antônio da Silva Moura

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 pro(..)

DOI: 10.21307/stattrans-2020-032

Published Online: 15-September-2020

A comparison of area level and unit level small area models in the presence of linkage errors

Loredana Di Consiglio/ Tiziana Tuoto

In Official Statistics, interest in data integration has grown enormously, but the effect of integration procedures on statistical analysis has not yet been sufficiently developed. Data integration is not an error-free procedure and linkage errors, as false links and missed links can invalidate standard estimates. Recently, increasing attention has been paid to the effect of linkage errors on the statistical analyses and on statistical predictions. Recently, methods to adjust the unit level smal(..)

DOI: 10.21307/stattrans-2020-033

Published Online: 15-September-2020

High dimensional, robust, unsupervised record linkage

Sabyasachi Bera/ Snigdhansu Chatterjee

We develop a technique for record linkage on high dimensional data, where the two datasets may not have any common variable, and there may be no training set available. Our methodology is based on sparse, high dimensional principal components. Since large and high dimensional datasets are often prone to outliers and aberrant observations, we propose a technique for estimating robust, high dimensional principal components. We present theoretical results validating the robust, high dimensional pri(..)

DOI: 10.21307/stattrans-2020-034

Published Online: 15-September-2020

Confidence bands for a distribution function with merged data from multiple sources

Takumi Saegusa

We consider nonparametric estimation of a distribution function when data are collected from multiple overlapping data sources. Main statistical challenges include (1) heterogeneity of data sets, (2) unidentified duplicated records across data sets, and (3) dependence due to sampling without replacement from a data source. The proposed estimator is computable without identifying duplication but corrects bias from duplicated records. We show the uniform consistency of the proposed estimator over (..)

DOI: 10.21307/stattrans-2020-035

Published Online: 15-September-2020

Model selection in radon data fusion

Xuze Zhang/ Saumyadipta Pyne/ Benjamin Kedem

Fitting parametric models or the use of the empirical cumulative distribution function are problematic when it comes to the estimation of tail probabilities from small samples. A possible remedy is to fuse or combine the small samples with additional data from external sources and base the inference on the so called density ratio model with variable tilt functions, which widens the support of the estimated distribution of interest. This approach is illustrated using residential radon concentrati(..)

DOI: 10.21307/stattrans-2020-036

Published Online: 15-September-2020

An evaluation of design-based properties of different composite estimators

Daniel Bonnéry/ Yang Cheng/ Partha Lahiri

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 matri(..)

DOI: 10.21307/stattrans-2020-037

Published Online: 15-September-2020

A generic business process model for conducting microsimulation studies

Jan Pablo Burgard/ Hanna Dieckmann/ Joscha Krause/ Hariolf Merkle/ Ralf Münnich/ Kristina M. Neufang/ Simon Schmaus

Microsimulations make use of quantitative methods to analyze complex phenomena in populations. They allow modeling socioeconomic systems based on micro-level units such as individuals, households, or institutional entities. However, conducting a microsimulation study can be challenging. It often requires the choice of appropriate data sources, micro-level modeling of multivariate processes, and the sound analysis of their outcomes. These work stages have to be conducted carefully to obtain relia(..)

DOI: 10.21307/stattrans-2020-038

Published Online: 15-September-2020

Applying data synthesis for longitudinal business data across three countries

M. Jahangir Alam/ Benoit Dostie/ Jörg Drechsler/ Lars Vilhuber

Data on businesses collected by statistical agencies are challenging to protect. Many businesses have unique characteristics, and distributions of employment, sales, and profits are highly skewed. Attackers wishing to conduct identification attacks often have access to much more information than for any individual. As a consequence, most disclosure avoidance mechanisms fail to strike an acceptable balance between usefulness and confidentiality protection. Detailed aggregate statistics by geograp(..)

DOI: 10.21307/stattrans-2020-039

Published Online: 15-September-2020

A general Bayesian approach to meet different inferential goals in poverty research for small areas

Partha Lahiri/ Jiraphan Suntornchost

Poverty mapping that displays spatial distribution of various poverty indices is most useful to policymakers and researchers when they are disaggregated into small geographic units, such as cities, municipalities or other administrative partitions of a country. Typically, national household surveys that contain welfare variables such as income and expenditures provide limited or no data for small areas. It is well-known that while direct survey-weighted estimates are quite reliable for national (..)

DOI: 10.21307/stattrans-2020-040

Published Online: 15-September-2020

No Record Found..
Page Actions