MSPE_JNR: JNR MSPE Estimator of Observed Best Predictor.

In rohosen/OBPSAE: Observed best predictors for small area estimation

Description

This function computes the MSPE estimator of Observed Best Predictor (OBP) proposed by Jiang, Nguyen and Rao (2011).

Usage

MSPE_JNR(formula, data, errorvar, theta.OBP, A.BPE, beta.BPE)

Arguments

formula	an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. The variables included in formula must have a length equal to the number of small areas. More about the model specification are given under Details.
data	optional data frame containing the variable names in formula.
errorvar	vector containing the variances of the random errors for all small areas.
theta.OBP	an optional vector of OBP values. See details.
A.BPE	optional BPE estimate of variance of random effects or the true value, if known. See details.
beta.BPE	optional BPE estimate of fixed effects coefficients. See details.

Details

formula is specified in the form response ~ predictors where the predictors are separated by +. formula has an implied intercept term. To remove the intercept term, use either y ~ x - 1 or y ~ 0 + x.

theta.OBP, A.BPE and beta.BPE are optional arguments. If any of them is missing, all three are computed from the data.

Value

This function will return a vector of the JNR MSPE estimator of the OBP.

References

Jiang J, Nguyen T, and Rao J. S. (2011), "Best Predictive Small Area Estimation", Journal of the American Statistical Association.

rohosen/OBPSAE documentation built on May 17, 2019, 2:22 p.m.