JOURNAL ARTICLE

Estimating the parameters of a doubly truncated normal distribution

Mukul Mohan MittalRam C. Dahiya

Year: 1987 Journal:   Communications in Statistics - Simulation and Computation Vol: 16 (1)Pages: 141-159   Publisher: Taylor & Francis

Abstract

Abstract This paper deals with the maximum likelihood estimation of parameters for a doubly truncated normal distribution when the truncation points are known. We prove, in this case, that the MLEs are nonexistent (become infinite) with positive probability. For estimators that exist with probability one, the class of Bayes modal estimators or modified maximum likelihood estimators is explored. Another useful estimating procedure, called mixed estimation, is proposed. Simulations compare the behavior of the MLEs, the modified MLEs, and the mixed estimators which reveal that the MLE, in addition to being nonexistent with positive probability, behaves poorly near the upper boundary of the interval of its existence. The modified MLEs and the mixed estimators are seen to be remarkably better than the MLE Keywords: maximum likelihood estimationBayes' modal estimation nonexistence of the estimator

Keywords:
Mathematics Estimator Truncation (statistics) Statistics Maximum likelihood Modal Distribution (mathematics) Interval (graph theory) M-estimator Maximum likelihood sequence estimation Applied mathematics Mathematical analysis Combinatorics

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14
Cited By
1.34
FWCI (Field Weighted Citation Impact)
12
Refs
0.77
Citation Normalized Percentile
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Citation History

Topics

Statistical Distribution Estimation and Applications
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Methods and Bayesian Inference
Physical Sciences →  Mathematics →  Statistics and Probability
Bayesian Methods and Mixture Models
Physical Sciences →  Computer Science →  Artificial Intelligence

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