A B C D E G H I L M N P Q R S T U V Z
Rstpm2-package | Flexible parametric survival models. |
addModel | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
aft | Parametric accelerated failure time model with smooth time functions |
aft-class | Class "stpm2" ~~~ |
aftModel | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
aft_integrated | Parametric accelerated failure time model with smooth time functions |
aft_integrated-class | Class "stpm2" ~~~ |
aft_mixture | Parametric accelerated failure time model with smooth time functions |
aft_mixture-class | Class "stpm2" ~~~ |
AIC-method | Class "pstpm2" |
AICc-method | Class "pstpm2" |
anova-method | Class "pstpm2" |
as.data.frame.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
as.data.frame.markov_msm_diff | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
as.data.frame.markov_msm_ratio | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
as.data.frame.markov_sde | Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models. |
bhazard | Placemarker function for a baseline hazard function. |
BIC-method | Class "pstpm2" |
brcancer | German breast cancer data from Stata. |
coef<- | Generic method to update the coef in an object. |
collapse_markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
colon | Colon cancer. |
confint.predictnl | Estimation of standard errors using the numerical delta method. |
cox.tvc | Test for a time-varying effect in the 'coxph' model |
diff | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
diff.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
eform | S3 method for to provide exponentiated coefficents with confidence intervals. |
eform-method | Class "pstpm2" |
eform-method | Class "stpm2" ~~~ |
eform.default | S3 method for to provide exponentiated coefficents with confidence intervals. |
eform.stpm2 | S3 method for to provide exponentiated coefficents with confidence intervals. |
grad | gradient function (internal function) |
gsm | Parametric and penalised generalised survival models |
gsm.control | Defaults for the gsm call |
gsm_design | Extract design information from an stpm2/gsm object and newdata for use in C++ |
hazFun | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
hrModel | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
incrVar | Utility that returns a function to increment a variable in a data-frame. |
legendre.quadrature.rule.200 | Legendre quadrature rule for n=200. |
lhs | Internal functions for the rstpm2 package. |
lhs<- | Internal functions for the rstpm2 package. |
lines-method | Class "pstpm2" |
lines-method | Class "stpm2" ~~~ |
lines.pstpm2 | S3 methods for lines |
lines.stpm2 | S3 methods for lines |
markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
markov_sde | Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models. |
nsx | Generate a Basis Matrix for Natural Cubic Splines (with eXtensions) |
nsxD | Generate a Basis Matrix for the first derivative of Natural Cubic Splines (with eXtensions) |
numDeltaMethod | Calculate numerical delta method for non-linear predictions. |
plot-method | Class "stpm2" ~~~ |
plot-method | Class "stpm2" ~~~ |
plot-method | Class "stpm2" ~~~ |
plot-method | plots for an stpm2 fit |
plot-method | Class "pstpm2" |
plot-method | Class "stpm2" ~~~ |
plot-method | Class '"tvcCoxph"' |
plot-methods | plots for an stpm2 fit |
plot.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
plot.markov_sde | Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models. |
popmort | Background mortality rates for the colon dataset. |
predict-method | Class "stpm2" ~~~ |
predict-method | Class "stpm2" ~~~ |
predict-method | Class "stpm2" ~~~ |
predict-method | Predicted values for an stpm2 or pstpm2 fit |
predict-methods | Predicted values for an stpm2 or pstpm2 fit |
predict.formula | Estimation of standard errors using the numerical delta method. |
predict.nsx | Evaluate a Spline Basis |
predictnl | Estimation of standard errors using the numerical delta method. |
predictnl-method | Class "stpm2" ~~~ |
predictnl-method | Class "stpm2" ~~~ |
predictnl-method | Class "stpm2" ~~~ |
predictnl-method | ~~ Methods for Function predictnl ~~ |
predictnl-method | Class "pstpm2" |
predictnl-method | Class "stpm2" ~~~ |
predictnl-methods | ~~ Methods for Function predictnl ~~ |
predictnl.default | Estimation of standard errors using the numerical delta method. |
predictnl.lm | Estimation of standard errors using the numerical delta method. |
print.predictnl | Estimation of standard errors using the numerical delta method. |
pstpm2 | Parametric and penalised generalised survival models |
pstpm2-class | Class "pstpm2" |
qAICc-method | Class "pstpm2" |
ratio_markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
rbind.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
residuals-method | Residual values for an stpm2 or pstpm2 fit |
residuals-methods | Residual values for an stpm2 or pstpm2 fit |
rhs | Internal functions for the rstpm2 package. |
rhs<- | Internal functions for the rstpm2 package. |
Rstpm2 | Flexible parametric survival models. |
simulate-method | Simulate values from an stpm2 or pstpm2 fit |
simulate-methods | Simulate values from an stpm2 or pstpm2 fit |
smoothpwc | Utility to use a smooth function in markov_msm based on piece-wise constant values |
splineFun | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
standardise | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
standardise.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
standardise.markov_sde | Predictions for continuous time, nonhomogeneous Markov multi-state models using Aalen's additive hazards models. |
stpm2 | Parametric and penalised generalised survival models |
stpm2-class | Class "stpm2" ~~~ |
subset.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
summary-method | Class "pstpm2" |
summary-method | Class "stpm2" ~~~ |
transform.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
tvcCoxph-class | Class '"tvcCoxph"' |
update-method | Methods for Function update |
update-methods | Methods for Function update |
vcov.markov_msm | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |
vuniroot | Vectorised One Dimensional Root (Zero) Finding |
zeroModel | Predictions for continuous time, nonhomogeneous Markov multi-state models using parametric and penalised survival models. |