| probtrans_fft {ebmstate} | R Documentation |
Compute subject-specific transition probabilities using a convolution algorithm based on the Fast Fourier transform.
Description
Compute subject-specific transition probabilities using a convolution algorithm based on the Fast Fourier transform.
Usage
probtrans_fft(initial_state, cumhaz, max_time, nr_steps = 10000)
Arguments
initial_state |
The present function estimates state occupation probabilities from the state given in this argument. |
cumhaz |
An |
max_time |
The maximum time for which transition probabilities are estimated. |
nr_steps |
The number of steps in the convolution algorithm (larger increases precision but makes it slower) |
Details
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.
For the same approximation grid, probtrans_fft doesn’t
always yield the same result as probtrans_ebmstate
(semi-Markov version), even though they are meant to approximate
exactly the same convolution. probtrans_ebmstate is
sensitive to the grid interval size, but not such much to the
maximum grid time. probtrans_fft is sensitive to both
these parameters, as referred above.
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.
Value
An object of class 'probtrans'. See the 'value'
section in the help page of mstate::probtrans.
Author(s)
Rui Costa