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Accession Number:
ADP007186
Title:
Approximations of the Normal-Logistic Convolution Integral,
Corporate Author:
NORTH CAROLINA STATE UNIV AT RALEIGH DEPT OF STATISTICS
Report Date:
1992-01-01
Abstract:
The normal-logistic convolution arises in several statistical applications, including logistic regression models and multinomial logit models. We begin by characterizing the logistic distribution as a scale mixture of normals. We then construct least maximum approximations of the logistic distribution function using finite discrete mixtures of normal dfs using the Remes algorithm. The convolution integral follows by convolving this approximation with the normal.
Supplementary Note:
This article is from 'Computing Science and Statistics: Proceedings of the Symposium on Interface Critical Applications of Scientific Computing (23rd): Biology, Engineering, Medicine, Speech Held in Seattle, Washington on 21-24 April 1991,' AD-A252 938, p445-447.
Pages:
0003
File Size:
0.00MB
