Many techniques in survey sampling depend on the possession of information about an auxiliary variable x, or a vector of auxiliary variables, available for the entire population. Regression estimates ...

Recently, analysis of variance (ANOVA) random effects models have been applied to data sets consisting of repeated measurements of pollutants within factories in order to identify determinants of ...

Under a linear regression model, the best linear unbiased estimator (BLUE) for a finite population total can be obtained. The problem studied here is that of estimating the variance for setting ...

This article was originally published on Built In by Eric Kleppen. Variance is a powerful statistic used in data analysis and machine learning. It is one of the four main measures of variability along ...

The SURVEYMEANS and SURVEYREG procedures perform statistical analysis for survey data. These analytical procedures take into account the design used to select the sample. The sample design can be a ...

Identify characteristics of “good” estimators and be able to compare competing estimators. Construct sound estimators using the techniques of maximum likelihood and method of moments estimation.

The SURVEYMEANS procedure uses the Taylor expansion method to estimate sampling errors of estimators based on complex sample designs. This method obtains a linear approximation for the estimator and ...

In this sense, the proposed method is an extension of the variance of the regression estimator for two-stage sampling. The method is applied to quarterly data from the Labor Force Survey where ...

The exponentially weighted moving average (EWMA) estimator is widely used to forecast the conditional volatility of short-horizon asset returns. The EWMA estimator is appropriate when returns are ...