Results 181 to 190 of about 543,870 (241)
Weighted likelihood negative binomial regression
, 2013 Amiguet, Michael +2 more
openaire +1 more source
Most Neuroscience Data Is Not Normally Distributed: Analyzing Your Data in a Non-normal World. [PDF]
eNeuroMalek-Ahmadi M, Reed AM, Guan DX.
europepmc +1 more source
Some of the next articles are maybe not open access.
Related searches:
Related searches:
2007
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with
J. Hilbe
semanticscholar +3 more sources
This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with
J. Hilbe
semanticscholar +3 more sources
The VGAM package for negative binomial regression
Australian & New Zealand Journal of Statistics, 2020Negative binomial (NB) regression is the most common full‐likelihood method for analysing count data exhibiting overdispersion with respect to the Poisson distribution. Usually most practitioners are content to fit one of two NB variants, however other important variants exist.
T. Yee
openaire +2 more sources
Chemical Engineering Research and Design, 2021
Wasim Iqbal, Yuk Ming Tang, Ka-Yin Chau
exaly +2 more sources
Wasim Iqbal, Yuk Ming Tang, Ka-Yin Chau
exaly +2 more sources
Poisson & Negative Binomial Regression
Bayes Rules!, 2022Alicia A. Johnson +2 more
openaire +2 more sources