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Posted 12-11-2017 02:55 AM
(2101 views)

Hi,

I was performing Linear Regression which is based on E-Commerce Dataset. I was stuck with the following problem.

1. Added constant to each value of Y and then taking the log.

2. Taking the square root of each value.

None of the above solutions is making Y variable normal. Please suggest how to move forward

2 REPLIES 2

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Moved question to " SAS Statistical Procedures"

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I assume that your response is positively valued except for the zeros. If that is correct, and if the values are all integers (like a count: 0, 1, 2, 3, ...), then you can fit a zero-inflated Poisson or negative binomial model using PROC GENMOD. See the GENMOD documentation. If the response is positive and continuous, then you could try fitting a zero-inflated gamma model using PROC FMM - for example:

```
data a;
call streaminit(2342);
do i=1 to 100;
y=rand("gamma",2);
output;
end;
do i=1 to 10; y=0; output; end;
run;
/* histogram of data */
proc sgplot data=a;
histogram y / showbins nbins=9;
run;
/* zero-inflated gamma model */
proc fmm data=a plots=density(nbins=9);
model y= / dist=gamma;
model + / dist=constant;
run;
```

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