Add to ORKGA resampling method is introduced to approximate, when some of the predictors are deleted, the quantiles of the distribution of the usual least squares pivots in linear regression. The approximation is used to construct confidence regions for the parameters of interest of the model
The problem of estimating the coefficients in a linear regression model is considered when some of t...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
A resampling method is introduced to approximate, when some of the predictors are deleted, the quant...
A res amp ling method is introduced to approximate the asymptotic distribution of the least squares ...
We will study here different resampling procedures for creating confidence sets in linear models. A ...
Abstract: In this paper, the hierarchical ways for building a regression model by using bootstrap an...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
Problem statement: Bootstrap approach had introduced new advancement in modeling and model evaluatio...
The application of the resampling-approach to the linear regression model analysis is considered. Th...
The application of the resampling-approach to the linear regression model analysis is considered. Th...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
We consider inference for linear regression models estimated by weighted-average least squares (WALS...
Linear regression is the most famous type of regression analysis in statistics. A statistical analys...
The bootstrap is a computationally intensive data analysis technique. It is particularly useful for ...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...
A resampling method is introduced to approximate, when some of the predictors are deleted, the quant...
A res amp ling method is introduced to approximate the asymptotic distribution of the least squares ...
We will study here different resampling procedures for creating confidence sets in linear models. A ...
Abstract: In this paper, the hierarchical ways for building a regression model by using bootstrap an...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
Problem statement: Bootstrap approach had introduced new advancement in modeling and model evaluatio...
The application of the resampling-approach to the linear regression model analysis is considered. Th...
The application of the resampling-approach to the linear regression model analysis is considered. Th...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
We consider inference for linear regression models estimated by weighted-average least squares (WALS...
Linear regression is the most famous type of regression analysis in statistics. A statistical analys...
The bootstrap is a computationally intensive data analysis technique. It is particularly useful for ...
The problem of estimating the coefficients in a linear regression model is considered when some of t...
Today increasing amounts of data are available for analysis purposes and often times for resource al...
A bootstrap method for generating confidence intervals in linear models is suggested. The method is ...