Type: | Package |
Title: | Conditional Aalen-Johansen Estimation |
Version: | 1.0 |
Maintainer: | Martin Bladt <martinbladt@math.ku.dk> |
Description: | Provides the conditional Nelson-Aalen and Aalen-Johansen estimators. The methods are based on Bladt & Furrer (2023), in preparation. |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
Encoding: | UTF-8 |
RoxygenNote: | 7.2.1 |
Suggests: | knitr, rmarkdown |
VignetteBuilder: | knitr |
NeedsCompilation: | no |
Packaged: | 2023-02-28 18:01:12 UTC; martinbladt |
Author: | Martin Bladt [aut, cre], Christian Furrer [aut] |
Repository: | CRAN |
Date/Publication: | 2023-03-01 10:42:09 UTC |
Compute the conditional Aalen-Johansen estimator.
Description
Compute the conditional Aalen-Johansen estimator.
Usage
aalen_johansen(
data,
x = NULL,
a = NULL,
p = NULL,
alpha = 0.05,
collapse = FALSE
)
Arguments
data |
A list of trajectory data for each individual. |
x |
A numeric value for conditioning. |
a |
A bandwidth. Default uses an asymmetric version using alpha. |
p |
An integer representing the number of states. The absorbing state is last. |
alpha |
A probability around the point x, for asymmetric sub-sampling. |
collapse |
Logical, whether to collapse the last state of the model. |
Value
A list containing the Aalen-Johansen estimator, the Nelson-Aalen estimator, and related quantities.
Calculate the product integral of a matrix function
Description
Calculate the product integral of a matrix function
Usage
prodint(start, end, step_size, lambda)
Arguments
start |
Start time. |
end |
End time. |
step_size |
Step size of the grid. |
lambda |
A given matrix function. |
Value
The product integral of the given matrix function.
Simulate the path of a time-inhomogeneous (semi-)Markov process until a maximal time
Description
Simulate the path of a time-inhomogeneous (semi-)Markov process until a maximal time
Usage
sim_path(i, rates, dists, t = 0, u = 0, tn = Inf, abs = numeric(0), bs = NA)
Arguments
i |
The initial state, integer. |
rates |
The total transition rates out of states, a function with arguments state (integer), time (numeric), and duration (numeric) returning a rate (numeric). |
dists |
The distribution of marks, a function with arguments state (integer), time (numeric), and duration (numeric) returning a probability vector. |
t |
The initial time, numeric. |
u |
The initial duration (since the last transition), numeric. By default equal to zero |
tn |
The maximal time, numeric. By default equal to inifinity |
abs |
Vector indicating which states are absorbing. By default the last state is absorbing. |
bs |
Vector of upper bounds on the total transition rates. By default the bounds are determined using optimize, which might only identify a local maximum. |
Value
A list concerning jump times and states, with the first time being the initial time t and state and the last time being tn (if not absorbed)
Examples
jump_rate <- function(i, t, u){if(i == 1){3*t} else if(i == 2){5*t} else{0}}
mark_dist <- function(i, s, v){if(i == 1){c(0, 1/3, 2/3)} else if(i == 2){c(1/5, 0, 4/5)} else{0}}
sim <- sim_path(sample(1:2, 1), t = 0, tn = 2, rates = jump_rate, dists = mark_dist)
sim