[R] Logistic regression for large data

[Bill Dunlap]

summary(Base)

would show if one of columns of Base was read as character data instead of
the expected numeric.  That could cause an explosion in the number of dummy
variables, hence a huge design matrix.

-Bill


On Fri, Nov 11, 2022 at 11:30 PM George Brida <georgebrida94 using gmail.com>
wrote:

> 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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