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smoothSurv (version 0.3-4)

Survival Regression with Smoothed Error Distribution

Description

This package contains primarily a function to fit a regression model with possibly right, left or interval censored observations and with the error distrbution expressed as a mixture of G-splines. Core part of the computation is done in compiled C++ written using the Scythe Statistical Libary Version 0.3.

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Version

Install

install.packages('smoothSurv')

Monthly Downloads

259

Version

0.3-4

License

GPL version 2 or newer

Maintainer

Arnost Komarek

Last Published

December 13th, 2023

Functions in smoothSurv (0.3-4)

c.to.a

Work Function for 'smoothSurvReg'
eval.Gspline

Evaluate a G-spline in a grid of values
give.c

Work Function for 'smoothSurvReg'
minPenalty

Minimize the penalty term under the two (mean and variance) constraints
derivative.cc3

Work Function for 'smoothSurvReg', currently nowhere used
smoothSurvReg.object

Smoothed Survival Regression Object
print.estimTdiff

Print for Objects of Class 'estimTdiff'
estimTdiff

Estimate expectation of survival times and their difference from the results given by survival regression function
MP.pseudoinv

Work Function for 'smoothSurvReg', currently nowhere used.
a.to.c

Work Function for 'smoothSurvReg'
fdensity.smoothSurvReg

Density for Objects of Class 'smoothSurvReg'
survfit.smoothSurvReg

Survivor Curves for Objects of Class 'smoothSurvReg'
piece

Left Continuous Piecewise Constant Function with a Finite Support.
find.c

Work Function for 'smoothSurvReg'
smoothSurvReg.control

More Options for 'smoothSurvReg'
plot.smoothSurvReg

Plot Objects of Class 'smoothSurvReg'
hazard.smoothSurvReg

Hazard Curves for Objects of Class 'smoothSurvReg'
standardized logistic

Density of Standardized Logistic Distribution.
smoothSurvReg

Regression for a Survival Model with Smoothed Error Distribution
residuals.smoothSurvReg

Residuals for Objects of Class 'smoothSurvReg'
print.smoothSurvReg

Summary and Print for Objects of Class 'smoothSurvReg'
derivative.expAD

Work Function for 'smoothSurvReg', currently nowhere used
smoothSurvReg.fit

Work Function to Fit the Model Using 'smoothSurvReg'
std.data

Standardization of the Data
extreme value

Density of the Extreme Value Distribution of a Minimum.