Displaying 5 results from an estimated 5 matches for "pahuja".
2004 Jun 22
3
Regression Modeling query
Hi All
I received a raw data set with one record per tennis player (both male and
female) and then i cured it by aggregation i.e by 4 age groups, 2 gender
levels and 6 income levels. Gender and Income are categorical variables.
Please advise me how to use 'R' to model this data set (Actually, i want to
know the right regression technique and steps to do that, including removing
2017 Nov 30
1
How to count instructions in a function?
...t; If I were you, I would write a ModulePass that uses the CallGraph analysis
> to get a call graph. I would then iterate over the nodes in the call graph
> and propagate information from callees to callers.
>
> Regards,
>
> John Criswell
>
>
> On 11/29/17 4:02 PM, Zubin Pahuja via llvm-dev wrote:
>
> Hello,
>
> I am trying to count IR instructions in a function for static analysis
> using llvm pass. In contrast with existing examples, I am trying to include
> instruction counts of all the callees of the function.
>
> Counting the instructions of a...
2017 Nov 29
2
How to count instructions in a function?
Hello,
I am trying to count IR instructions in a function for static analysis
using llvm pass. In contrast with existing examples, I am trying to include
instruction counts of all the callees of the function.
Counting the instructions of a function is easy using passes, but iterating
through the module's CallGraph is proving to be confusing. I believe I have
to use CallGraphWrapperPass to
2004 Jun 11
1
Regression query : steps for model building
Hi
I have a set of data with both quantitative and categorical predictors.
After scaling of response variable, i looked for multicollinearity (VIF
values) among the predictors and removed the predictors who were hinding
some of the
other significant predictors. I'm curious to know whether the predictors
(who are not significant) while doing simple 'lm' will be involved in
2004 Jun 11
4
Regression query
Hi
I have a set of data with both quantitative and categorical predictors.
After scaling of response variable, i looked for multicollinearity (VIF
values)
among the predictors and removed the predictors who were hinding some of the
other significant
predictors. I'm curious to know whether the predictors (who are not
significant)
while doing simple 'lm' will be involved in