Hi, everyone,
I am sorry that my last E-mail showed as messy code. So I send it again. 

I have one question about the Poisson regression.

   I have three data frames: X, Y and Z. I want to quantify the relative contributions of Y and Z to the variation of X using variation partitioning method. However, the X only has one column (500 rows) and contains some zero values (about 90 rows are zero), while both Y and Z contain three explanatory variables for each. As I know, the variation partitioning method is based on the linear regression model when the response data table only has one column. Can I use the variation partitioning method directly? Or should I use the Poisson regression method because many zero values are included in my response data table? Adjusted r-square is not available in Poisson regression; instead, we can only get a pseudo r-square. Furthermore, I have not found that Poisson regression contains partial regression algorithm to quantify the relative importance of two explanatory data table. Therefore, if I have to use the Poisson regression, how can I achieve my aim?

Thanks for any help and best wishes for you!

 

Lin

July 30th, 2012

 
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