PredictSample: predict or restrict a mesh or matrix based on a statistical...

In zarquon42b/RvtkStatismo: Integrating statismo and R using the vtkStandardMeshRepresenter

Description

predict or restrict a mesh or matrix based on a statistical model

Usage

PredictSample(model, dataset, representer = TRUE, ...)

## S4 method for signature 'pPCA,matrix'
PredictSample(model, dataset, representer = TRUE,
  origSpace = TRUE, lmDataset = NULL, lmModel = NULL, sdmax = NULL,
  mahaprob = c("none", "chisq", "dist"), align = TRUE, addNoise = FALSE,
  posteriorMean = FALSE, ptValueNoise = 1, ...)

## S4 method for signature 'pPCA,mesh3d'
PredictSample(model, dataset, representer = TRUE,
  origSpace = TRUE, lmDataset = NULL, lmModel = NULL, sdmax = NULL,
  mahaprob = c("none", "chisq", "dist"), align = TRUE, addNoise = FALSE,
  posteriorMean = FALSE, ptValueNoise = 1, ...)

## S4 method for signature 'pPCA,missing'
PredictSample(model, dataset, representer = TRUE,
  origSpace = TRUE, lmDataset = NULL, lmModel = NULL, sdmax = NULL,
  mahaprob = c("none", "chisq", "dist"), align = TRUE, addNoise = FALSE,
  posteriorMean = FALSE, ptValueNoise = 1, ...)

Arguments

model	model of class pPCA
dataset	a matrix or a mesh3d. If dataset is missing, lmDataset and lmModel need to be provided and the posterior mean will be returned.
representer	if TRUE and the model contains a representer mesh, a surface mesh will be returned, coordinate matrix otherwise.
...	currently not in use.
origSpace	logical: rotate the estimation back into the original coordinate system.
lmDataset	optional: landmarks on the dataset used for alignment.
lmModel	optional: landmarks on the model's mean used for alignment.
sdmax	maximum allowed standard deviation (per Principal axis) within the model space. Defines the probabilistic boundaries.
mahaprob	character: if != "none", use mahalanobis-distance to determine overall probability (of the shape projected into the model space."chisq" uses the Chi-Square distribution of the squared Mahalanobisdistance, while "dist" restricts the values to be within a multi-dimensional sphere of radius sdmax. If FALSE the probability will be determined per PC separately.
align	if TRUE, the sample will be aligned to the mean.
addNoise	re-add noise while reprojecting from latent into shape space.
posteriorMean	if TRUE, instead the shape will be the mean of the posterior model using the coordinates defined by lmModel and lmDataset.
ptValueNoise	numeric: set global noise assumed in the data when posteriorMean = TRUE

Value

PredictSample returns a matrix/mesh3d restricted to the boundaries given by the modelspace.

See Also

StatismoModelMembers

zarquon42b/RvtkStatismo documentation built on May 4, 2019, 9:09 p.m.