Add to ORKGA new and very fast method of bootstrap for sampling without replacement from a finite population is proposed. This method can be used to estimate the variance in sampling with unequal inclusion probabilities and does not require artificial populations or utilization of bootstrap weights. The bootstrap samples are directly selected from the original sample. The bootstrap procedure contains two steps: in the first step, units are selected once with Poisson sampling using the same inclusion probabilities as the original design. In the second step, amongst the non-selected units, half of the units are randomly selected twice. This procedure enables us to efficiently estimate the variance. A set of simulations show the advantages of this new re...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
Since bootstrap samples are simple random samples with replacement from the original sample, the inf...
Sampling is one of the most fundamental concepts in statistics, as the quality and accuracy of the s...
A new and very fast method of bootstrap for sampling without replacement from a finite population is...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
In this paper, a new resampling technique for sampling designs with unequal inclusion probabilities ...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
This Phd deals with Bootstrap methods for finite population sampling. The first chapter introduces s...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is esse...
Bootstrap method is a popular tool for numerically assessing estimatorsâ accuracy, confidence int...
Consider a finite population from which the stratified sample with simple random sample without repl...
Bootstrap is one of the resampling statistical methods. This method was proposed by B. Efron. The ma...
In complex survey sampling every population unit is assigned a specific probability to be included ...
In this paper, a new resampling technique for sampling designs with unequal inclusion probabilities ...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
Since bootstrap samples are simple random samples with replacement from the original sample, the inf...
Sampling is one of the most fundamental concepts in statistics, as the quality and accuracy of the s...
A new and very fast method of bootstrap for sampling without replacement from a finite population is...
In complex designs, classical bootstrap methods result in a biased variance estimator when the samp...
In this paper, a new resampling technique for sampling designs with unequal inclusion probabilities ...
Bootstrap is a useful tool for making statistical inference, but it may provide erroneous results un...
This Phd deals with Bootstrap methods for finite population sampling. The first chapter introduces s...
Not Availablea new boot~trap technique of variance estimation for complex survey data known as "Res...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is esse...
Bootstrap method is a popular tool for numerically assessing estimatorsâ accuracy, confidence int...
Consider a finite population from which the stratified sample with simple random sample without repl...
Bootstrap is one of the resampling statistical methods. This method was proposed by B. Efron. The ma...
In complex survey sampling every population unit is assigned a specific probability to be included ...
In this paper, a new resampling technique for sampling designs with unequal inclusion probabilities ...
In this paper, we propose a method that estimates the variance of an imputed estimator in a multista...
Since bootstrap samples are simple random samples with replacement from the original sample, the inf...
Sampling is one of the most fundamental concepts in statistics, as the quality and accuracy of the s...