Response modeling methodology (RMM)—maximum likelihood estimation procedures-Reference-Cited by-同舟云学术

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Response modeling methodology (RMM)—maximum likelihood estimation procedures

Published:2005-06 Issue:4 Volume:49 Page:1148-1172
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Shore Haim

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference16 articles.

1. Applied Regression Including Computing and Graphics;Cook,1999

2. Weibull Analysis;Dodson,1994

3. Fitting Statistical distributions;Karian,2000

4. Generalized Linear Models, with Applications in Engineering and the Sciences;Myers,2002

5. Observations of high dispersion clusters of galaxies;Oegerle;The Astronom. J.,1995

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1. Comparison of development methodologies in web applications;Information and Software Technology;2020-03

2. Response modeling methodology;WIREs Computational Statistics;2011-03-25

3. Comparison of linear predictors obtained by data transformation, generalized linear models (GLM) and response modeling methodology (RMM);Quality and Reliability Engineering International;2008

4. Profit Maximizing Warranty Period with Sales Expressed by a Demand Function;Quality and Reliability Engineering International;2007

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