Finite population prediction under a linear function superpopulation model:a bayesian perspective
| Autor: | Josemar Rodrigues, Heleno Bolfarine |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
Statistics and Probability
education.field_of_study Variables Observational error media_common.quotation_subject Population Bayesian probability Regression analysis Conditional probability distribution Bayesian inference Statistics PESQUISA E PLANEJAMENTO ESTATÍSTICO education Mathematics media_common Population variance |
| Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP |
| ISSN: | 1532-415X 0361-0926 |
| DOI: | 10.1080/03610929008830335 |
| Popis: | Exact and approximate Bayesian inference is developed for the prediction problem in finite populations under a linear functional superpopulation model. The models considered are the usual regression models involving two variables, X and Y, where the independent variable X is measured with error. The approach is based on the conditional distribution of Y given X and our predictor is the posterior mean of the quantity of interest (population total and population variance) given the observed data. Empirical investigations about optimal purposive samples and possible model misspecifications based on comparisons with the corresponding models where X is measured without error are also reported. |
| Databáze: | OpenAIRE |
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