weibullregpost: Log posterior of a Weibull proportional odds model for...
In LearnBayes: Functions for Learning Bayesian Inference
Description
Usage
Arguments
Value
Author(s)
Examples
Description
Computes the log posterior density of (log sigma, mu, beta) for a Weibull
proportional odds regression model
Usage
1
weibullregpost(theta,data)
Arguments
theta
vector of parameter values log sigma, mu, and beta
data
data matrix with columns survival time, censoring variable, and covariate matrix
Value
value of the log posterior
Author(s)
Jim Albert
Examples
1
2
3
4
5
data(chemotherapy)
attach(chemotherapy)
d=cbind(time,status,treat-1,age)
theta=c(-.6,11,.6,0)
weibullregpost(theta,d)
LearnBayes documentation built on May 1, 2019, 7:03 p.m.
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Description Usage Arguments Value Author(s) Examples
Description
Computes the log posterior density of (log sigma, mu, beta) for a Weibull proportional odds regression model
Usage
1 | weibullregpost(theta,data)
|
Arguments
theta |
vector of parameter values log sigma, mu, and beta |
data |
data matrix with columns survival time, censoring variable, and covariate matrix |
Value
value of the log posterior
Author(s)
Jim Albert
Examples
1 2 3 4 5 | data(chemotherapy)
attach(chemotherapy)
d=cbind(time,status,treat-1,age)
theta=c(-.6,11,.6,0)
weibullregpost(theta,d)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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