| Name : R-ungroup
| |
| Version : 1.4.4
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp156.1.1
| Date : 2024-09-10 02:59:23
|
| Group : Development/Libraries/Other
| Source RPM : R-ungroup-1.4.4-lp156.1.1.src.rpm
|
| Size : 0.76 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data
|
Description :
Versatile method for ungrouping histograms (binned count data) assuming
that counts are Poisson distributed and that the underlying sequence on
a fine grid to be estimated is smooth. The method is based on the
composite link model and estimation is achieved by maximizing a
penalized likelihood. Smooth detailed sequences of counts and rates are
so estimated from the binned counts. Ungrouping binned data can be
desirable for many reasons: Bins can be too coarse to allow for
accurate analysis; comparisons can be hindered when different grouping
approaches are used in different histograms; and the last interval is
often wide and open-ended and, thus, covers a lot of information in the
tail area. Age-at-death distributions grouped in age classes and
abridged life tables are examples of binned data. Because of modest
assumptions, the approach is suitable for many demographic and
epidemiological applications. For a detailed description of the method
and applications see Rizzi et al. (2015) < doi:10.1093/aje/kwv020>.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.6/x86_64 |
