## An Introduction to Model-Based Survey Sampling with ApplicationsThis text brings together important ideas on the model-based approach to sample survey, which has been developed over the last twenty years. Suitable for graduate students and professional statisticians, it moves from basic ideas fundamental to sampling to more rigorous mathematical modelling and data analysis and includes exercises and solutions. |

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An Introduction to Model-Based Survey Sampling with Applications Ray Chambers,Robert Clark Limited preview - 2012 |

An Introduction to Model-Based Survey Sampling with Applications Ray Chambers,Robert Clark No preview available - 2012 |

An Introduction to Model-Based Survey Sampling with Applications Ray Chambers,Robert Clark No preview available - 2012 |

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ˆtEy ˆtRy ˆtSy ˆty approach approximately area effects assume auxiliary variable balanced sampling bias correction biased BLUP weights bootstrap calibration Chapter clusters corresponding defined denote domain EB predictor EBLUP efficient equal expected value finite population homogenous model inference linear model linear population model linear predictor matrix mean squared error methods minimise misspecification model-based non-informative non-parametric non-sample outlier robust population elements population mean population total ty population units population values prediction interval prediction variance predictor of ty random variable ratio population model regression RMSE robust estimator sample data sample design sample outliers sample sizes sample survey sample units sample values sample weights Section selected simple random sampling small area estimation specification Statistical strata stratified expansion estimator stratum h survey sampling survey variable Table unbiased estimator vector wiyi wNPs Y-values zero