| Type: | Package |
| Title: | Boosting Multistate Models |
| Version: | 1.1.88 |
| Date: | 2022-05-06 |
| Author: | Holger Reulen |
| Maintainer: | Holger Reulen <hreulen@uni-goettingen.de> |
| Description: | Contains infrastructure for using mboost::gamboost() in order to estimate multistate models. |
| Imports: | mboost (≥ 2.2-2) |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Packaged: | 2022-05-06 05:27:25 UTC; hsennhenn |
| Repository: | CRAN |
| Date/Publication: | 2022-05-06 07:00:13 UTC |
Component-wise Functional Gradient Descent Boosting of Multi State Models
Description
Gradient boosting for Cox-type multi state models: minimization of negative partial log likelihood using component- and transition-wise base-learners.
Details
This package provides function objects to fit Cox-type multi state models
using the functional gradient descent boosting algorithm as implemented in the
splendid package mboost. Therefore, function Family() for fitting
multi state models is given, including negative log partial likelihood of a
Cox-type multi state model as risk function and its negative first partial
derivative with respect to the linear predictor as working response function.
Author(s)
Holger Reulen
References
Andersen, P. K., Borgan, O., Gill, R. D., Keiding, N. (1993) Statistical Models Based on Counting Processes. Springer Series in Statistics, New York: Springer-Verlag.
Buehlmann, P. Hothorn, T. (2007) Boosting Algorithms: Regularization, Prediction and Model Fitting (with Discussion). Statistical Science, 22(4), p. 477–505.
Hothorn, T., Buehlmann, P., Kneib, T., Schmid, M., Hofner, B. (2012) mboost: Model-Based Boosting, R package version 2.2-0. http://CRAN.R-project.org/package=mboost.
Kneib, T., Hothorn, T., Tutz, G. (2009) Variable Selection and Model Choice in Geoadditive Regression Models. BIOMETRICS 65, p. 626–634.
Ridgeway, G. (1999) The state of boosting. Computing Science and Statistics 31, p. 172–181.
See Also
mboost
Breslow estimator for cumulative baseline hazard rate
Description
This function calculates the Breslow estimator for the cumulative baseline hazard rate, given fitted linear predictor values.
Usage
breslow(f, riskset, entry, exit, trans, event)
Arguments
f |
fitted linear predictor values |
riskset |
riskset list as generated by |
entry |
entry times. |
exit |
exit times. |
trans |
transition index. |
event |
observed event indicator. |
Details
This function calculates the Breslow estimator for the cumulative baseline hazard rate, given fitted linear predictor values.
Value
A list of length Q with each element including including elements
times |
a vector of observed event times, |
cbhr |
a vector of calculated cumulative hazard rate values. |
Author(s)
Holger Reulen
Examples
## Not run: breslow(f, riskset, entry, exit, trans, event)
Calculation of risksets
Description
Calculates risksets needed for using family multistate.
Usage
buildrisksets(entry, exit, trans, event, statusinfo)
Arguments
entry |
a vector with entry times. |
exit |
a vector with exit times. |
trans |
a vector with transition types. |
event |
a vector with noncensoring event indicators. |
statusinfo |
a logical indicating if information on the calculation process should be printed. |
Details
This function calculates riksets needed for family multistate.
Value
A list of length 2 with elements Ci and Ri, each
vectors of length n.
Author(s)
Holger Reulen
Cross-validation for Boosting Multi-state Models
Description
Cross-validation for Boosting Multi-state Models.
Usage
cvriskMSM(m, d, id, formulaMSM, xlist, qlist, k, riskset)
Arguments
m |
... |
d |
... |
id |
... |
formulaMSM |
... |
xlist |
... |
qlist |
... |
k |
... |
riskset |
... |
Details
...
Value
...
Author(s)
Holger Reulen
Degrees of Freedom
Description
This function calculates the degrees of freedom as part of the calculation of the Akaike Information Criterion (AIC).
Usage
degreesoffreedom(m, statusinfo)
Arguments
m |
a boosted multi state model. |
statusinfo |
a logical indicating if information on the calculation process should be printed. |
Details
This function calculates the degress of freedom as part of the calculation of the Akaike Information Criterion.
Value
A vector of length equal to the number of boosting iterations in the plugged in model object.
Author(s)
Holger Reulen
Examples
## Not run: degreesoffreedom(m, statusinfo)
...
Description
...
Usage
helpfunctionmultistate1(x, ef)
Arguments
x |
... |
ef |
... |
Details
...
Author(s)
Holger Reulen
Examples
## Not run: helpfunctionmultistate1(x, ef)
...
Description
...
Usage
helpfunctionmultistate2(x, dummy)
Arguments
x |
... |
dummy |
... |
Details
...
Author(s)
Holger Reulen
Examples
## Not run: helpfunctionmultistate2(x, dummy)
Mean Centering with Taking Care of the Transition Type(s)
Description
...
Usage
meancentering(d, x, q, x.name, q.name)Arguments
d |
data set |
x |
covariate |
q |
transition type(s) |
x.name |
name of the covariate for pasting the new transition type specific covariate name |
q.name |
name of the transition type for pasting the new transition type specific covariate name |
Details
...
Value
...
Author(s)
Holger Reulen
Family for Multistate Models
Description
This function implements a family for
fitting multistate models using mboost.
Usage
multistate(Ri, Ci)
Arguments
Ri |
a list giving the individual (i.e., spell specific) risksets. |
Ci |
a list giving the indexes of risksets an individual spell is a part of (see page 213 in the book Generalized Additive Models by T.J. Hastie and R.J. Tibshirani for a description). |
Details
This function implements a family for multistate models and
will be used inside the gamboost or glmboost function.
Value
Functions to be used inside gamboost.
Author(s)
Holger Reulen
...
Description
...
Usage
plloss(event, f, Ri)Arguments
event |
... |
f |
... |
Ri |
... |
Details
...
Value
...
Author(s)
Holger Reulen
Plot Cross-validation for Boosting Multi-state Models
Description
Plot cross-validation for boosting multi-state models.
Usage
plotcvriskMSM(cvriskMSMobject, type)
Arguments
cvriskMSMobject |
result from |
type |
should all stratified results be plotted ( |
Details
...
Value
...
Author(s)
Holger Reulen