| Name : R-detectseparation
| |
| Version : 0.3
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp155.6.1
| Date : 2024-07-01 11:38:48
|
| Group : Development/Libraries/Other
| Source RPM : R-detectseparation-0.3-lp155.6.1.src.rpm
|
| Size : 0.26 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Detect and Check for Separation and Infinite Maximum Likelihood Estimates
|
Description :
Provides pre-fit and post-fit methods for detecting separation and
infinite maximum likelihood estimates in generalized linear models with
categorical responses. The pre-fit methods apply on binomial-response
generalized liner models such as logit, probit and cloglog regression,
and can be directly supplied as fitting methods to the glm() function.
They solve the linear programming problems for the detection of
separation developed in Konis (2007,
< https://ora.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a>)
using \'ROI\' < https://cran.r-project.org/package=ROI> or \'lpSolveAPI\'
< https://cran.r-project.org/package=lpSolveAPI>. The post-fit methods
apply to models with categorical responses, including binomial-response
generalized linear models and multinomial-response models, such as
baseline category logits and adjacent category logits models; for
example, the models implemented in the \'brglm2\'
< https://cran.r-project.org/package=brglm2> package. The post-fit
methods successively refit the model with increasing number of
iteratively reweighted least squares iterations, and monitor the ratio
of the estimated standard error for each parameter to what it has been
in the first iteration. According to the results in Lesaffre & Albert
(1989, < https://www.jstor.org/stable/2345845>), divergence of those
ratios indicates data separation.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.5/x86_64 |
