Estimation of mean squared error of model-based estimators of small area means under a nested error linear regression model

Estimation of the mean squared error of predictors of small area linear parameters under a logistic mixed model

An accuracy measure (mean squared error, MSE) is necessary when small area estimators of linear parameters are provided. Even in the case when such estimators arise from the assumption of relatively simple models for the variable of interest, as linear mixed models, the analytic form of the MSE is not suitable to be calculated explicitly. Some good and widely used approximations are available f...

متن کامل

Nonnegative mean squared prediction error estimation in small area estimation

Small area estimation has received enormous attention in recent years due to its wide range of application, particularly in policy making decisions. The variance based on direct sample size of small area estimator is unduly large and there is a need of constructing model based estimator with low mean squared prediction error (MSPE). Estimation of MSPE and in particular the bias correction of MS...

متن کامل

Nonparametric estimation of mean-squared prediction error in nested-error regression models

Nested-error regression models are widely used for analyzing clustered data. For example, they are often applied to two-stage sample surveys, and in biology and econometrics. Prediction is usually the main goal of such analyses, and mean-squared prediction error is the main way in which prediction performance is measured. In this paper we suggest a new approach to estimating mean-squared predic...

متن کامل

Nonparametric Estimation of Mean-squared Prediction Error in Nested-error Regression Models by Peter Hall

Nested-error regression models are widely used for analyzing clustered data. For example, they are often applied to two-stage sample surveys, and in biology and econometrics. Prediction is usually the main goal of such analyses, and mean-squared prediction error is the main way in which prediction performance is measured. In this paper we suggest a new approach to estimating mean-squared predic...

متن کامل

Non-parametric bootstrap mean squared error estimation for M-quantile estimators of small area averages, quantiles and poverty indicators

Small area estimation is conventionally concerned with the estimation of small area averages and totals. More recently emphasis has been also placed on the estimation of poverty indicators and of key quantiles of the small area distribution function using robust models for example, the M-quantile small area model (Chambers and Tzavidis, 2006). In parallel to point estimation, Mean Squared Error...

متن کامل

Estimation of mean squared error of model-based estimators of small area means under a nested error linear regression model

نویسندگان

چکیده

منابع مشابه

Estimation of the mean squared error of predictors of small area linear parameters under a logistic mixed model

Nonnegative mean squared prediction error estimation in small area estimation

Nonparametric estimation of mean-squared prediction error in nested-error regression models

Nonparametric Estimation of Mean-squared Prediction Error in Nested-error Regression Models by Peter Hall

Non-parametric bootstrap mean squared error estimation for M-quantile estimators of small area averages, quantiles and poverty indicators

ژورنال