A method for fitting regression models to data that exhibit spatial correlation and Heteroskedasticity is proposed. A combination of parametric and nonparametric regression techniques is used to iteratively estimate the various components of the model. The approach is demonstrated on a large...

type="main" xml:id="sjos12045-abs-0001" <title type="main">ABSTRACT</title>Small area estimation has long been a popular and important research topic due to its growing demand in public and private sectors. We consider here the basic area level model, popularly known as the Fay–Herriot model. Although much of current...

Over the last decade, new information has been developed and collected to measure the extent of food insecurity and hunger in the United States. Common measurement of the phenomenon of hunger and food insecurity has become possible through efforts of the U.S. Department of Agriculture (USDA) to...

This paper reviews the statistical properties of the model used to obtain estimates of the prevalence and severity of poverty-linked food insecurity and hunger in the United States. The U.S. Department of Agriculture has annually sponsored data collection efforts to obtain information on food...

The authors propose a method for fitting regression models to data that exhibit spatial correlation and heteroskedasticity. A combination of parametric and nonparametric regression techniques is used to iteratively estimate the various components of the model. The approach is demonstrated on a...