| Name : R-overdisp
| |
| Version : 0.1.2
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.5
| Date : 2024-06-14 11:11:07
|
| Group : Development/Libraries/Other
| Source RPM : R-overdisp-0.1.2-lp153.1.5.src.rpm
|
| Size : 0.02 MB
| |
| Packager : (none)
| |
| Summary : Overdispersion in Count Data Multiple Regression Analysis
|
Description :
Detection of overdispersion in count data for multiple regression
analysis. Log-linear count data regression is one of the most popular
techniques for predictive modeling where there is a non-negative
discrete quantitative dependent variable. In order to ensure the
inferences from the use of count data models are appropriate,
researchers may choose between the estimation of a Poisson model and a
negative binomial model, and the correct decision for prediction from a
count data estimation is directly linked to the existence of
overdispersion of the dependent variable, conditional to the
explanatory variables. Based on the studies of Cameron and Trivedi
(1990) < doi:10.1016/0304-4076(90)90014-K> and Cameron and Trivedi
(2013, ISBN:978-1107667273), the overdisp() command is a contribution
to researchers, providing a fast and secure solution for the detection
of overdispersion in count data. Another advantage is that the
installation of other packages is unnecessary, since the command runs
in the basic R language.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
