BAYESIAN SAMPLE SIZE COMPUTING FOR NORMAL DISTRIBUTION VIA LOWEST POSTERIOR LOSS INTERVALS

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NAJAFI N.; BEVRANI H.

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Journal: JOURNAL OF STATISTICAL SCIENCES Year:2010 | Volume:4 | Issue:1 Page(s): 77-88

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Information Journal Paper

Title

BAYESIAN SAMPLE SIZE COMPUTING FOR NORMAL DISTRIBUTION VIA LOWEST POSTERIOR LOSS INTERVALS

Author(s)

NAJAFI N. | BEVRANI H. | Issue Writer Certificate

Keywords

BAYESIAN INFERENCEQ2

QUADRATIC LOSS FUNCTIONQ3

LOWEST POSTERIOR LOSSQ3

Abstract

This paper is devoted to compute the sample size for estimation of Normal distribution mean with Bayesian approach. The QUADRATIC LOSS FUNCTION is considered and three criterions are applied to obtain p- tolerance regions with the LOWEST POSTERIOR LOSS. These criterions are: average length, average coverage and worst outcome. The proposed methodology is examined, and its effectiveness is shown.

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APA: Copy

NAJAFI, N., & BEVRANI, H.. (2010). BAYESIAN SAMPLE SIZE COMPUTING FOR NORMAL DISTRIBUTION VIA LOWEST POSTERIOR LOSS INTERVALS. JOURNAL OF STATISTICAL SCIENCES, 4(1), 77-88. SID. https://sid.ir/paper/124115/en

Vancouver: Copy

NAJAFI N., BEVRANI H.. BAYESIAN SAMPLE SIZE COMPUTING FOR NORMAL DISTRIBUTION VIA LOWEST POSTERIOR LOSS INTERVALS. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2010;4(1):77-88. Available from: https://sid.ir/paper/124115/en

IEEE: Copy

N. NAJAFI, and H. BEVRANI, “BAYESIAN SAMPLE SIZE COMPUTING FOR NORMAL DISTRIBUTION VIA LOWEST POSTERIOR LOSS INTERVALS,” JOURNAL OF STATISTICAL SCIENCES, vol. 4, no. 1, pp. 77–88, 2010, [Online]. Available: https://sid.ir/paper/124115/en

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