Description Usage Arguments Value Author(s) Examples
View source: R/glmPredictPhotoZ.R
glmPredictPhotoZ
computes a list of simple summary
statistics for the photometric redshift estimation.
1 | glmPredictPhotoZ(data, train)
|
data |
a data.frame containing the data one wished to compute the redshift |
train |
a trained glm object containing the fit of the model |
list containing the results of the redshift estimation
Rafael S. de Souza, Alberto Krone-Martins
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## 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)
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