title | author | date | output |
---|---|---|---|
Generalized Linear Models for Astronomy |
Rafael S. de Souza. |
August 14th, 2014 |
pdf_document |
CosmoGLM is available from github. The current development version can be installed using devtools.
library(devtools)
install_github("CosmoR", username="RafaelSdeSouza", subdir="CosmoGLM")
This is an R Markdown document to explain in simple terms the use of Generalized Linear Models into Astronomy reproducing the main results from Rafael S. de Souza et al (2014).
Reading the data
Set working directory to the data folder (replace by your own directory)
data_path<-"/Users/rafael/Dropbox/artigos/Meusartigos/IAA-WGC/GLMs/Simulation/data/"
Biffi_data<-read.table(file=paste(data_path,"Biffi2014.csv",sep=""),
header=TRUE)
Biffi_original<-Biffi_data
Problem 1: xmol, Z, SFR. SFR is the response variable
Biffi_data<-Biffi_data[,c("SFR","Xmol","Z")]
Transforming variable into numeric (required by GLM packages)
Biffi_data$SFR[which(Biffi_data$SFR==0)]<-0
Biffi_data$SFR[which(Biffi_data$SFR>0)]<-1
Biffi_data$SFR<-as.numeric(Biffi_data$SFR)
Biffi_data$Z<-scale(Biffi_data$Z)#Scaling and centering
Biffi_data$Xmol<-scale(Biffi_data$Xmol)#Scaling and centering
Frequentist
Fglm <-glm(SFR~Z+Xmol,family=binomial(link="logit"),
data = Biffi_data)
plotProb(Fglm)+ylab("Predicted Probabilities for SF")+xlab("")+
ggtitle("Frequentist Logistic Regression")+coord_cartesian(ylim = c(0,1.05))