probtrans_fft: Compute subject-specific transition probabilities using a...
In gerstung-lab/ebmstate: Empirical Bayes Multi-State Cox Model

Description Usage Arguments Details Value Author(s) See Also

Compute subject-specific transition probabilities using a convolution algorithm based on the Fast Fourier transform.

1	probtrans_fft(initial_state, cumhaz, time)

`initial_state`	The present function estimates state occupation probabilities from the state given in this argument.
`cumhaz`	An `msfit` object created by running `mstate` or `mstate_generic`.
`time`	A vector of positive and increasing time points starting from and including zero.

The time argument is crucial for precision. The density of time points and the upper time limit should be increased until the estimated curves become stable. A useful rule of thumb is to set the upper time limit to a time point in which the probability of each transient state is zero and the probability of each absorbing state is constant.

The algorithm behind probtrans_ebmstate is based on the convolution of density and survival functions and is suitable for processes with a tree-like transition structure only.

An object of class 'probtrans'. See the 'value' section in the help page of mstate::probtrans.

Rui Costa

probtrans;

gerstung-lab/ebmstate documentation built on Feb. 11, 2022, 4:01 p.m.