Package: smoothSurv 2.7

Arnošt Komárek

smoothSurv: Survival Regression with Smoothed Error Distribution

Contains, as a main contribution, a function to fit a regression model with possibly right, left or interval censored observations and with the error distribution expressed as a mixture of G-splines. Core part of the computation is done in compiled 'C++' written using the 'Scythe' Statistical Library Version 0.3. The methods implemented in the package have been published in Komárek, Lesaffe and Hilton (2005, J. of Comp. and Graph. Stat.) <doi:10.1198/106186005X63734> and Lesaffre, Komárek and Declerck (2005, Stat. Methods in Med. Res.) <doi:10.1191/0962280205sm417oa>.

Authors:Arnošt Komárek [aut, cre], Kevin M. Quinn [ctb, cph], Andrew D. Martin [ctb, cph], Daniel B. Pemstein [ctb, cph], Berwin A. Turlach [ctb]

smoothSurv_2.7.tar.gz
smoothSurv_2.7.zip(r-4.7-x86_64)smoothSurv_2.7.zip(r-4.7-arm64)smoothSurv_2.7.zip(r-4.6-x86_64)smoothSurv_2.7.zip(r-4.6-arm64)
smoothSurv_2.7.tar.gz(r-4.7-arm64)smoothSurv_2.7.tar.gz(r-4.7-x86_64)smoothSurv_2.7.tar.gz(r-4.6-arm64)smoothSurv_2.7.tar.gz(r-4.6-x86_64)
smoothSurv_2.7.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smoothSurv/json (API)

# Install 'smoothSurv' in R:

install.packages('smoothSurv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.78 score 2 packages 385 downloads 20 exports 3 dependencies

Last updated from:45075d966c. Checks:10 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	123
linux-devel-x86_64	OK	144
source / vignettes	OK	254
linux-release-arm64	OK	129
linux-release-x86_64	OK	133
windows-devel-arm64	OK	214
windows-devel-x86_64	OK	171
windows-release-arm64	OK	240
windows-release-x86_64	OK	142
wasm-release	OK	127

Exports:a2c c2a derivative.cc3 derivative.expAD dextreme dstextreme dstlogis estimTdiff eval.Gspline fdensity find.c give.c hazard minPenalty MP.pseudoinv piece smoothSurvReg smoothSurvReg.control smoothSurvReg.fit std.data

Dependencies:lattice Matrix survival

Help page	Topics
Confidence Intervals for Regression Parameters of 'smoothSurvReg' Model	confint.smoothSurvReg
Estimate expectation of survival times and their difference from the results given by survival regression function	estimTdiff estimTdiff.smoothSurvReg
Evaluate a G-spline in a grid of values	eval.Gspline
Density of the Extreme Value Distribution of a Minimum.	dextreme dstextreme
Density for Objects of Class 'smoothSurvReg'	fdensity fdensity.smoothSurvReg
Hazard Curves for Objects of Class 'smoothSurvReg'	hazard hazard.smoothSurvReg
Minimize the penalty term under the two (mean and variance) constraints	minPenalty
Left Continuous Piecewise Constant Function with a Finite Support.	piece
Plot Objects of Class 'smoothSurvReg'	plot.smoothSurvReg
Print for Objects of Class 'estimTdiff'	print.estimTdiff
Summary and Print for Objects of Class 'smoothSurvReg'	print.smoothSurvReg summary.smoothSurvReg
Residuals for Objects of Class 'smoothSurvReg'	residuals.smoothSurvReg
Regression for a Survival Model with Smoothed Error Distribution	C_smoothSurvReg84 smoothSurvReg
More Options for 'smoothSurvReg'	smoothSurvReg.control
Work Function to Fit the Model Using 'smoothSurvReg'	smoothSurvReg.fit
Smoothed Survival Regression Object	smoothSurvReg.object
Density of Standardized Logistic Distribution.	dstlogis
Standardization of the Data	std.data
Survivor Curves for Objects of Class 'smoothSurvReg'	survfit.smoothSurvReg

Package: smoothSurv 2.7

smoothSurv: Survival Regression with Smoothed Error Distribution

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)