Publication detail

Bootstrap approach to bias reduction

Authors: Kubanová Jana | Linda Bohdan | Černohorský Jan

Year: 2005

Type of publication: článek ve sborníku

Name of source: Bankacilik ve sigortacilik enstitüsü ile bankacilik ve sigortacilik yüksekokulu

Publisher name: Marmara University, Istanbul, Turkey

Place: Istanbul, Turecko

Page from-to: 10

Titles:

Language	Name	Abstract	Keywords
cze	Přístup bootstrap k ovlivnění redukce	Jedním z důležitých předpokladů ke správnému bodovému odhadu a následné statistické analýze je malý rozdíl mezi parametry a odhahy těchto parametrů, to znamená "malé" odchylky. Tento problém je významný u náhodného výběru malého rozsahu.	Bootstrap;statistická analýza;parametr
eng	Bootstrap approach to bias reduction	One of important presumption of the correct point estimate and subsequent statistical analysis is small difference between a parameter and a mean of this parameter`s estimate, it means ?small? bias. The problem is serious at random samples with small size. The bootstrap method can help to solve this problem; it can be used to bias reduction of any estimator obtained from a finite random sample. The objective is to gain a point estimate of the parameter t that can be expressed as a smooth function of population moments. Population moments are replaced by sample moments. Taylor series are used in the econometric model. Bias reduction will be demonstrated by examples. The bias estimate and the bias corrected estimator are depending on the number of simulation for the parameters. We want to see in the picture that the values of bias changed or not after simulations and reduced and no reduced values of bias and estimates of mean square error (MSE). To compare bias of the estimate and bias of corrected estimators for different types of the function is made the same calculations.	Bootstrap;statistical analysis;parameter

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