| Name : R-DBModelSelect
| |
| Version : 0.2.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.1.5
| Date : 2024-06-14 10:58:08
|
| Group : Development/Libraries/Other
| Source RPM : R-DBModelSelect-0.2.0-lp153.1.5.src.rpm
|
| Size : 0.04 MB
| |
| Packager : (none)
| |
| Summary : Distribution-Based Model Selection
|
Description :
Perform model selection using distribution and probability-based
methods, including standardized AIC, BIC, and AICc. These standardized
information criteria allow one to perform model selection in a way
similar to the prevalent \"Rule of 2\" method, but formalize the method
to rely on probability theory. A novel goodness-of-fit procedure for
assessing linear regression models is also available. This test relies
on theoretical properties of the estimated error variance for a normal
linear regression model, and employs a bootstrap procedure to assess
the null hypothesis that the fitted model shows no lack of fit. For
more information, see Koeneman and Cavanaugh (2023) < arXiv:2309.10614>.
Functionality to perform all subsets linear or generalized linear
regression is also available.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
