[R] Logistic regression for large data

[Ebert,Timothy Aaron]

Hi George,
   I did not get an attachment.
   My first step would be to try simplifying things. Do all of these work?

fit_1=glm(Base[,2]~Base[,1],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,10],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,11],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,12],family=binomial(link="logit"))
fit_1=glm(Base[,2]~Base[,13],family=binomial(link="logit"))

This is not a large dataset. That said, if your computer is nearly out of memory, even a small dataset might be too much. It might have plenty of physical memory, but also lots of (open files, cookies, applications, other stuff) that eat memory.

Regards,
Tim



-----Original Message-----
From: R-help <r-help-bounces using r-project.org> On Behalf Of George Brida
Sent: Friday, November 11, 2022 4:17 PM
To: r-help using r-project.org
Subject: [R] Logistic regression for large data

[External Email]

Dear R users,

I have a database  called Base.csv   (attached to this email) which
contains 13 columns and 8257 rows and whose the first 8 columns are dummy variables which take 1 or 0. The problem is when I wrote the following instructions to do a logistic regression , R runs for hours and hours without giving an output:

Base=read.csv("C:\\Users\\HP\\Desktop\\New\\Base.csv",header=FALSE,sep=";")
fit_1=glm(Base[,2]~Base[,1]+Base[,10]+Base[,11]+Base[,12]+Base[,13],family=binomial(link="logit"))

Apparently, there is not enough memory to have the requested output. Is there any other function for logistic regression that handle large data and return output in reasonable time.

Many thanks

Kind regards

George
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