Compute MSPE Estimates for the Fay Herriot Model and Nested Error Regression Model

Documentation for package ‘saeMSPE’ version 1.0

saeMSPE-package	Compute MSPE Estimates for the Fay Herriot Model and Nested Error Regression Model
mspeFHdb	Compute MSPE through double bootstrap method for Fay Herriot model
mspeFHjack	Compute MSPE through Jackknife method for Fay Herriot model
mspeFHlnr	Compute MSPE through linearization method for Fay Herriot model
mspeFHmcjack	Compute MSPE through Monte-Carlo jackknife method for Fay Herriot model
mspeFHpb	Compute MSPE through parameter bootstrap method for Fay Herriot model
mspeFHsumca	Compute MSPE through Sumca method for Fay Herriot model
mspeNERdb	Compute MSPE through double bootstrap(DB) method for Nested error regression model
mspeNERjack	Compute MSPE through resampling method for Nested error regression model
mspeNERlnr	Compute MSPE through linearization method for Nested error regression model
mspeNERmcjack	Compute MSPE through resampling method for Nested error regression model
mspeNERpb	Compute MSPE through parameter bootstrap method for Nested error regression model
mspeNERsumca	Compute MSPE through Sumca method for Nested error regression model
saeMSPE	Compute MSPE Estimates for the Fay Herriot Model and Nested Error Regression Model
varner	Estimates of the variance component using several methods for Nested error regression model.
varOBP	Estimate of the variance component using best predictive estimation method (BPE, also called OBP method) for Fay Herriot model.