CosmoPhotoz (version 0.1)

glmPredictPhotoZ: Predict photometric redshifts using a given glm fit object

Description

glmPredictPhotoZ computes a list of simple summary statistics for the photometric redshift estimation.

Usage

glmPredictPhotoZ(data, train)

Arguments

data

a data.frame containing the data one wished to compute the redshift

train

a trained glm object containing the fit of the model

Value

list containing the results of the redshift estimation

Examples

## Not run: 
# # Load the data
# data(PHAT0train)
# data(PHAT0test)
# 
# # Combine the training and test data and calculate the principal components
# PC_comb <- computeCombPCA(subset(PHAT0train, select=c(-redshift)),
#            subset(PHAT0test, select=c(-redshift)),
#            robust=FALSE) # robust is false here just to make it faster
# Trainpc <- cbind(PC_comb$x, redshift=PHAT0train$redshift)
# Testpc <- PC_comb$y
# 
# # Fitting
# Fit <- glmTrainPhotoZ(Trainpc, formula=redshift~poly(Comp.1,2)*
#            poly(Comp.2,2)*Comp.3*Comp.4*Comp.5*Comp.6,
#            method="Bayesian", family="gamma")
# 
# # Perform the photo-z estimation using the glmPredictPhotoZ function
# photoz <- glmPredictPhotoZ(data=Testpc, train=Fit$glmfit)
# specz <- PHAT0test$redshift
# 
# # Show a plot with the results
# plotDiagPhotoZ(photoz$photoz, specz, "box")
# ## End(Not run)