Temat: Bias - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Estimation of Population Mean Using Two Auxiliary Sources in Sample Surveys
Autorzy:: Shukla, Diwakar
Pathak, Sharad
Thakur, Narendra Singh
Powiązania:: https://bibliotekanauki.pl/articles/465744.pdf
Data publikacji:: 2012
Wydawca:: Główny Urząd Statystyczny
Tematy:: Family of estimators
SRSWOR
Bias and Mean squared error
Opis:: This paper proposes families for estimation of population mean of the main variable under study using the information on two different auxiliary variables under simple random sampling without replacement (SRSWOR) scheme. Three different classes of estimators are constructed, examined with a complete study with other existing estimators. The expression for bias and mean squared error of the proposed families are obtained up to first order of approximation. Usual ratio estimator, product estimator, dual to ratio estimator, ratio-cum-product type estimator and many more estimators are identified as particular members of the suggested family. Expressions of optimization are derived and theoretical results are supported by numerical examples.
Źródło:: Statistics in Transition new series; 2012, 13, 1; 21-36
1234-7655
Pojawia się w:: Statistics in Transition new series
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Missing data estimation based on the chaining technique in survey sampling
Autorzy:: Singh Thakur, Narendra
Shukla, Diwakar
Powiązania:: https://bibliotekanauki.pl/articles/2156986.pdf
Data publikacji:: 2022-12-15
Wydawca:: Główny Urząd Statystyczny
Tematy:: estimation
missing data
chaining
imputation
bias
mean squared error (MSE)
factor type (F-T)
chain type estimator
double sampling
Opis:: Sample surveys are often affected by missing observations and non-response caused by the respondents' refusal or unwillingness to provide the requested information or due to their memory failure. In order to substitute the missing data, a procedure called imputation is applied, which uses the available data as a tool for the replacement of the missing values. Two auxiliary variables create a chain which is used to substitute the missing part of the sample. The aim of the paper is to present the application of the Chain-type factor estimator as a means of source imputation for the non-response units in an incomplete sample. The proposed strategies were found to be more efficient and bias-controllable than similar estimation procedures described in the relevant literature. These techniques could also be made nearly unbiased in relation to other selected parametric values. The findings are supported by a numerical study involving the use of a dataset, proving that the proposed techniques outperform other similar ones.
Źródło:: Statistics in Transition new series; 2022, 23, 4; 91-111
1234-7655
Pojawia się w:: Statistics in Transition new series
Dostawca treści:: Biblioteka Nauki