subrank (version 0.9.9.3)

predonfly: Probability forecasting

Description

From two sets of observations, first one of complete observations and second one of incomplete observations, provides simulated values of the unknown coordinates.

Usage

predonfly(completeobs,incompleteobs,varnames,subsampsize,nbpreds=1,mixties=FALSE,
          maxtirs=1e5,complete=TRUE,nthreads=2)

Value

the matrix of the completed observations

Arguments

completeobs

the set of complete observations.

incompleteobs

the set of incomplete observations.

varnames

the modeled variables.

subsampsize

the sub-sample size.

nbpreds

the number of predictions for each incomplete observation.

mixties

if TRUE, should put equal weight on tied values, using random permutations (not yet implemented)

maxtirs

the maximum number of sub-samples, to stop the computation even if they did not provide nbpreds predictions for each incomplete observation.

complete

If TRUE, predictions are completed with incomplete observations

nthreads

number of number of threads, assumed to be strictly positive. For "full throttle" computations, consider using parallel::detectCores()

Author

Jerome Collet

Examples

lon=100
plon=30
subsampsize=10

x=rnorm(lon)
y=2*x+rnorm(lon)*0
donori=as.data.frame(cbind(x,y))
##
knownvalues=data.frame(x=rnorm(plon))
prev <- predonfly(donori,knownvalues,c("x","y"),subsampsize,100)

##
plot(prev$x,prev$y,pch=20,cex=0.5,
     ylim=range(c(prev$y,donori$y),na.rm=TRUE),xlim=range(c(prev$x,donori$x)))
points(donori[,1:2],col='red',pch=20,cex=.5)

lon=3000
mg=20
dimtot=4
rayon=6

genboules <- function(lon,a,d)
{
  ss <- function(vec)
  {return(sum(vec*vec))}
  surface=matrix(nrow=lon,ncol=d,data=rnorm(lon*d))
  rayons=sqrt(apply(surface,1,ss))
  surface=surface/rayons
  return(matrix(nrow=lon,ncol=d,data=rnorm(lon*d))+a*surface)
}

##############

donori=genboules(lon,rayon,dimtot)
donori=as.data.frame(donori)

dimconnues=3:dimtot
valconnues=matrix(nrow=1,ncol=length(dimconnues),data=0)
valconnues=as.data.frame(valconnues)
names(valconnues)=names(donori)[3:dimtot]
prev <- predonfly(donori,valconnues,names(donori),subsampsize,100)

boule2=genboules(plon,rayon,2)

plot(boule2[,1:2],xlab='X1',ylab='X2',pch=20,cex=.5)
plot(prev$V1,prev$V2,xlab='X1',ylab='X2',pch=20,cex=.5)