MHPropWithIWishart: Random walk Metropolis–Hastings algorithm for Sigma
In feng-li/movingknots: Efficient Bayesian multivariate surface regression
Description
Usage
Arguments
Value
Author(s)
View source: R/algorithms__MHPropWithIWishart.R
Description
Details are available in the paper.
Usage
1
2
3
4
5
6
7
8
9
10
11
MHPropWithIWishart(
param.cur,
logpost.fun.name,
Params,
Y,
x0,
callParam,
splineArgs,
priorArgs,
Params_Transform
)
Arguments
param.cur
NA
logpost.fun.name
NA
Params
NA
Y
NA
x0
NA
callParam
NA
splineArgs
NA
priorArgs
NA
Params_Transform
NA
Value
NA
Author(s)
Feng Li, Department of Statistics, Stockholm University, Sweden.
feng-li/movingknots documentation built on March 30, 2021, 11:58 a.m.
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.
Description Usage Arguments Value Author(s)
View source: R/algorithms__MHPropWithIWishart.R
Description
Details are available in the paper.
Usage
1 2 3 4 5 6 7 8 9 10 11 | MHPropWithIWishart(
param.cur,
logpost.fun.name,
Params,
Y,
x0,
callParam,
splineArgs,
priorArgs,
Params_Transform
)
|
Arguments
param.cur |
NA |
logpost.fun.name |
NA |
Params |
NA |
Y |
NA |
x0 |
NA |
callParam |
NA |
splineArgs |
NA |
priorArgs |
NA |
Params_Transform |
NA |
Value
NA
Author(s)
Feng Li, Department of Statistics, Stockholm University, Sweden.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.