Add to ORKGFunded by collage st. innovative projects This paper combines the least squaress estimate, least absolute deviation estimate, least median estimate with Bootstrap method. When the overall error distribution is unknown or it is not the normal distribution, we estimate the regression co-efficient and confidence interval of coefficient, and through data simulation, obtain Bootstrap method, which can improve stability of regression coefficient and reduce the length of confidence interval
Abstract: In this paper, the hierarchical ways for building a regression model by using bootstrap an...
At present very little is known about inference procedures on the parameters of the minimum sum of a...
The introduction of the bootstrap methods by Efron (1979) enables many empirical researches, which w...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
<pre><em>Statistical analysis which aims to analyze a linear relationship between the independent va...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Aim of this thesis is to introduce the reader to the basic bootstrap techniques used in econometrics...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
Background: Bootstrap is a computer simulation-based method that provides estimation accuracy in est...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Problem statement: Bootstrap approach had introduced new advancement in modeling and model evaluatio...
The purpose of this study is to demonstrate the use of the bootstrap method to perform statistical i...
This thesis is a study of Estimators, particularly in Linear Models. The newest technology of Bootst...
Abstract: In this paper, the hierarchical ways for building a regression model by using bootstrap an...
At present very little is known about inference procedures on the parameters of the minimum sum of a...
The introduction of the bootstrap methods by Efron (1979) enables many empirical researches, which w...
Regression models are the statistical methods that widely used in many fields. The models allow rela...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
<pre><em>Statistical analysis which aims to analyze a linear relationship between the independent va...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Aim of this thesis is to introduce the reader to the basic bootstrap techniques used in econometrics...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
The Bootstrap is the most widely used resampling statistical method. This method becomes very popula...
Background: Bootstrap is a computer simulation-based method that provides estimation accuracy in est...
The bootstrap is a method for estimating the distribution of an estimator or test statistic by resam...
Problem statement: Bootstrap approach had introduced new advancement in modeling and model evaluatio...
The purpose of this study is to demonstrate the use of the bootstrap method to perform statistical i...
This thesis is a study of Estimators, particularly in Linear Models. The newest technology of Bootst...
Abstract: In this paper, the hierarchical ways for building a regression model by using bootstrap an...
At present very little is known about inference procedures on the parameters of the minimum sum of a...
The introduction of the bootstrap methods by Efron (1979) enables many empirical researches, which w...