Try this:
First of all:
> predict(foo)
Error in UseMethod("predict") : no applicable method for "predict"
Therefore, an alternative approach may be taken:
As per: bar <- apply(foo,2,mean)
bar[1] is the intercept
bar[2] is the coefficient for x1
bar[2] is the coefficient for x2
Then calculate:
predictedVal <- bar[1] + bar[2] * x1 + bar[2] * x2
Thanks,
Deb
>>> Noah Silverman <n...@smartmediacorp.com> 22/09/2009 2:05 pm >>>
Deb,
That's great!!!
But, then how to I convert those values to a "model" so I can use a
"predict" function.
I can see:
bar <- apply(foo,2,mean)
That creates an object, "bar", with the coefficients.
But, I can't call predict on bar...
-N
On 9/21/09 7:58 PM, Debabrata Midya wrote:
> Try this:
> apply(foo, 2, mean) or
> apply(foo, 2, median)
> Thanks,
> Deb
>
> >>> Noah Silverman <n...@smartmediacorp.com> 22/09/2009 12:34 pm >>>
> Hi,
>
> I've been testing some models with the MCMCpack library.
>
> I can run the process and get a nice model "object". I can easily see
> the summary and even plot it.
>
> I can't seem to figure out how to:
> 1) Access the final coefficients in the model
> 2) Turn the coefficients into a model so I can then run predictions
> using them.
>
> A summary command will SHOW Me the coefficients, but I can't run a
> "predict" with them. Can someone suggest how to pull them out and
> format them so that I can run some predictions to test the quality. I
> thought something like "as.model" would be there, but isn't.
>
> For example.
>
> foo <- MCMClogit(label ~ x1 + x2)
>
> summary(foo)
> plot(foo)
>
> foo has all the info. How do I pull out the coefficients and format
> them into a "standard" logit model??
>
> Thanks!
>
> -N
>
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