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August 1, 1988Journal of Statistical Computation and Simulation120 citations

Imputation using markov chains

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KLKim-hung LiChinese University of Hong Kong

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Abstract

Broadly speaking, imputation means filling in incomplete values. A theoretically sound method is to impute the incomplete values through sampling from their predictive distribution. In this paper, an iterative imputation procedure, based on the idea of Markov chain, is proposed. Examples are presented to illustrate its applications.

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Cite This Study

Kim-hung Li (1988) studied this question.

synapsesocial.com/papers/6a1c06f501af05bf0da90ccchttps://doi.org/10.1080/00949658808811085
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Also Consider

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  1. 1The Calculation of Posterior Distributions by Data Augmentation1987 · 736 citations
  2. 2Lecture Notes on Limit Theorems for Markov Chain Transition Probabilities1971 · 154 citations
  3. 3Monte Carlo sampling methods using Markov chains and their applications1970 · 15,338 citations
  4. 4Practical Tests for Comparing Two Proportions with Incomplete Data1982 · 43 citations
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