| Name : R-minb
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.1.5
| Date : 2024-06-14 11:21:51
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| Group : Development/Libraries/Other
| Source RPM : R-minb-0.1.0-lp153.1.5.src.rpm
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| Size : 0.05 MB
| |
| Packager : (none)
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| Summary : Multiple-Inflated Negative Binomial Model
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Description :
Count data is prevalent and informative, with widespread application in
many fields such as social psychology, personality, and public health.
Classical statistical methods for the analysis of count outcomes are
commonly variants of the log-linear model, including Poisson regression
and Negative Binomial regression. However, a typical problem with count
data modeling is inflation, in the sense that the counts are evidently
accumulated on some integers. Such an inflation problem could distort
the distribution of the observed counts, further bias estimation and
increase error, making the classic methods infeasible. Traditional
inflated value selection methods based on histogram inspection are easy
to neglect true points and computationally expensive in addition.
Therefore, we propose a multiple-inflated negative binomial model to
handle count data modeling with multiple inflated values, achieving
data-driven inflated value selection. The proposed approach provides
simultaneous identification of important regression predictors on the
target count response as well. More details about the proposed method
are described in Li, Y., Wu, M., Wu, M., & Ma, S. (2023)
< arXiv:2309.15585>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
