example_raw_proj: Workflow for primitive method, with projections

In Infusion: Inference Using Simulation

Workflow for primitive method, with projections

Description

Example of the workflow with add_simulation), implementing the method described in the original publication (Rousset et al. 2017 <doi:10.1111/1755-0998.12627>), modified to use projectors.

Examples

if (Infusion.getOption("example_maxtime")>117) {
## Normal(mu,sd) model, with inefficient raw summary statistics:
## To illustrate that case we transform normal random deviates rnorm(,mu,sd)
## so that the mean of transformed sample is not sufficient for mu,
## and the variance of transformed sample is not sufficient for sd.
blurred <- function(mu,s2,sample.size) {
  s <- rnorm(n=sample.size,mean=mu,sd=sqrt(s2))
  s <- exp(s/4)
  return(c(mean=mean(s),var=var(s)))
}

set.seed(123)
dSobs <- blurred(mu=4,s2=1,sample.size=20) ## stands for the actual data to be analyzed

## Sampling design as in canonical example 
parsp <- init_grid(lower=c(mu=2.8,s2=0.4,sample.size=20),
                      upper=c(mu=5.2,s2=2.4,sample.size=20))
# simulate distributions
dsimuls <- add_simulation(,Simulate="blurred", parsTable=parsp) 

## Use projection to construct better summary statistics for each each parameter 
mufit <- project("mu",stats=c("mean","var"),data=dsimuls)
s2fit <- project("s2",stats=c("mean","var"),data=dsimuls)

## apply projections on simulated statistics
corrSobs <- project(dSobs,projectors=list("MEAN"=mufit,"VAR"=s2fit))
corrSimuls <- project(dsimuls,projectors=list("MEAN"=mufit,"VAR"=s2fit))

## Analyze 'projected' data as any data (cf canonical example)
densb <- infer_logLs(corrSimuls,stat.obs=corrSobs) 

} else data(densb)
#########
if (Infusion.getOption("example_maxtime")>10) {
slik <- infer_surface(densb) ## infer a log-likelihood surface
slik <- MSL(slik) ## find the maximum of the log-likelihood surface
}
if (Infusion.getOption("example_maxtime")>500) {
slik <- refine(slik,10, update_projectors=TRUE) ## refine iteratively
}

Infusion documentation built on Sept. 30, 2024, 9:16 a.m.