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ungroup
View on CRAN: Click
here
Download and install ungroup package within the R console
Install from CRAN:
install.packages("ungroup")
Install from Github:
library("remotes")
install_github("cran/ungroup")
Install by package version:
library("remotes")
install_version("ungroup", "1.4.4")
Attach the package and use:
library("ungroup")
Maintained by
Marius D. Pascariu
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-09-03
Latest Update: 2021-06-28
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>.
How to cite:
Marius D. Pascariu (2018). ungroup: Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data. R package version 1.4.4, https://cran.r-project.org/web/packages/ungroup
Previous versions and publish date:
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Other R packages that ungroup depends,
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Functions, R codes and Examples using
the ungroup R package
Some associated functions: AIC.pclm . AIC.pclm2D . BIC.pclm . BIC.pclm2D . MortSmooth_bbase . MortSmooth_tpower . build_B_spline_basis . build_C_matrix . build_P_matrix . compute_standard_errors . control.pclm . control.pclm2D . create.artificial.bin . delete.artificial.bin . frac . map.bins . ofun . optimize_par . pclm.confidence.dx . pclm.confidence.mx . pclm.confidence . pclm.fit . pclm.input.check . pclm . pclm2D . plot.pclm . plot.pclm2D . print.pclm . print.pclm2D . print.summary.pclm . print.summary.pclm2D . print.ungroup.data . residuals.pclm . residuals.pclm2D . seqlast . suggest.valid.out.step . summary.pclm . summary.pclm2D . ungroup.data . ungroup . validate.nlast .
Some associated R codes: MortalitySmooth_fun.R . RcppExports.R . pclm_1D.R . pclm_2D.R . pclm_CI.R . pclm_control.R . pclm_fit.R . pclm_graphics.R . pclm_optim.R . ungroup-data.R . utils.R . Full ungroup package functions and examples
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