Is there is one possibility to do regression on the data through data-transformation? If yes, what kind of transformation I can do?
Thanks.
Some more info about the X and Y variables would be a lot of help. Looking at the plot that accompanied your post, I didn't see much but noise. The X variable looks to get very large, so a plot of Y vs. log(X) might be revealing. I don't think there is going to be anything, but you might look at PROC TRANSREG for Box-Cox transformations as a step towards something.
Steve Denham
If the X axis is reversed, this looks like a classic case of heteroskedastic data in which the variance increases with X.
I'd define Z = 1/X and plot Y vs. Z (or use 1/(X+1) if X=0 is a possible value).
You can then use all the standard variance stabilizing transformations (AKA, normalizing transformations) such as Z-->log(Z) or Z-->sqrt(Z).
Depending on the meaning of X, you could also try just a simple reflection such as W = 300000 - x and then work with W.
As Steve mentions, transformations often work best when they are meaningfully related to the data. So ask yourself, is "natural" way to flip around the X axis?
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