Creates a template for a model in PSM

Description

Creates a template with R-syntax to help setup a model in PSM.

Usage

  PSM.template(Linear=FALSE,dimX=2,dimY=3,dimU=4,dimEta=5,file="")

Arguments

Value

None (invisible NULL).

Note

For further details please also read the package vignette pdf-document by writing vignette("PSM") in R.

Author(s)

Stig B. Mortensen and S<c3><b8>ren Klim

References

Please visit http://www.imm.dtu.dk/psm or refer to the help page for PSM.

See Also

PSM, PSM.estimate, PSM.smooth, PSM.template

Examples

# Linear model with input, random effects and dose
PSM.template(Linear=TRUE,dimX=1,dimY=2,dimU=3,dimEta=4)

# Non-linear model without input, random effects and dose
PSM.template(Linear=FALSE,dimX=1,dimY=2,dimU=0,dimEta=0)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(PSM)
Loading required package: MASS
Loading required package: numDeriv
Loading required package: deSolve

Attaching package: 'deSolve'

The following object is masked from 'package:graphics':

    matplot

Loading required package: ucminf
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/PSM/PSM.template.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PSM.template
> ### Title: Creates a template for a model in PSM
> ### Aliases: PSM.template
> ### Keywords: htest models multivariate ts
> 
> ### ** Examples
> 
> # Linear model with input, random effects and dose
> PSM.template(Linear=TRUE,dimX=1,dimY=2,dimU=3,dimEta=4)


MyModel <- vector(mode="list")
MyModel$Matrices=function(phi) {
  list(
       matA=matrix(c(  ), nrow=1, ncol=1),
       matB=matrix(c(  ), nrow=1, ncol=3),
       matC=matrix(c(  ), nrow=2, ncol=1),
       matD=matrix(c(  ), nrow=1, ncol=3)
       )
}
MyModel$h = function(eta,theta,covar) {
  phi <- theta
  phi
}
MyModel$S = function(phi) {
  matrix(c(  ), nrow=2, ncol=2)
}
MyModel$SIG = function(phi) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$X0 = function(Time,phi,U) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$ModelPar = function(THETA) {
  list(theta=list(  ),
       OMEGA=matrix(c(  ), nrow=4, ncol=4)
       )
}


> 
> # Non-linear model without input, random effects and dose
> PSM.template(Linear=FALSE,dimX=1,dimY=2,dimU=0,dimEta=0)


MyModel <- vector(mode="list")
MyModel$Functions$f = function(x,u,time,phi) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$Functions$df = function(x,u,time,phi) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$Functions$g = function(x,u,time,phi) {
  matrix(c(  ), nrow=2, ncol=1)
}
MyModel$Functions$dg = function(x,u,time,phi) {
  matrix(c(  ), nrow=2, ncol=1)
}
MyModel$h = function(eta,theta,covar) {
  phi <- theta
  phi
}
MyModel$S = function(u,time,phi) {
  matrix(c(  ), nrow=2, ncol=2)
}
MyModel$SIG = function(u,time,phi) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$X0 = function(Time,phi,U) {
  matrix(c(  ), nrow=1, ncol=1)
}
MyModel$ModelPar = function(THETA) {
  list(theta=list(  ))
}


> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>