predictnl-methods: Estimation of standard errors using the numerical delta...

In rstpm2: Smooth Survival Models, Including Generalized Survival Models

Estimation of standard errors using the numerical delta method.

Description

A simple, yet exceedingly useful, approach to estimate the variance of a function using the numerical delta method. A number of packages provide functions that analytically calculate the gradients; we use numerical derivatives, which generalises to models that do not offer analytical derivatives (e.g. ordinary differential equations, integration), or to examples that are tedious or error-prone to calculate (e.g. sums of predictions from GLMs).

Usage

## S4 method for signature 'mle2'
predictnl(object, fun, newdata=NULL, gd=NULL, ...)
## S4 method for signature 'stpm2'
predictnl(object, fun, newdata=NULL,
    link = c("I", "log", "cloglog", "logit"), gd=NULL, ...)
## S4 method for signature 'pstpm2'
predictnl(object, fun, newdata=NULL,
    link = c("I", "log", "cloglog", "logit"), gd=NULL, ...)
## S4 method for signature 'aft'
predictnl(object, fun, newdata=NULL,
    link = c("I", "log", "cloglog", "logit"), gd=NULL, ...)

Arguments

object	An object with coef, vcov and `coef<-` methods (required).
fun	A function that takes object as the first argument, possibly with newdata and other arguments (required). See notes for why it is often useful to include newdata as an argument to the function.
newdata	An optional argument that defines newdata to be passed to fun.
link	A character string to represent the link on which to calculate the variance and confidence intervals.
gd	An optional matrix of gradients. If this is not specified, then the gradients are calculated using finite differences.
...	Other arguments that are passed to fun.

Details

The confidence interval estimation is based on the delta method using numerical differentiation.

Value

A data-frame with components Estimate, lower and upper, with an attribute "newdata" for the newdata data-frame.

Methods

object= "stpm2"

an stpm2 fit

See Also

stpm2

rstpm2 documentation built on Aug. 28, 2025, 1:10 a.m.