[R] locfit smoothing question (package maintainer not reachable)

[David Winsemius]

That is what I thought to be the critical paragraph. The variance is  
assumed to be = 1 when you use family="gaussian" rather than the  
default of family="qgauss". You give it a vector, 1000*rnorm(100),  
that ranges widely and a small (relative) variance is assumed and so  
the confidence intervals are plotted as very narrow. This does not  
seem surprising given the functions documented design. I have the book  
and do not think I even need to pull it off the shelf since the help  
pages appear fully informative in this instance. I get an rv of 1 with  
the "gaussian" option and an rv of nearly 1000 when the default is used.

-- 
David Winsemius


On Mar 3, 2009, at 3:26 PM, Suresh Krishna wrote:

>
> David Winsemis wrote:
>
>> I think you should read (or re-read)  the locfit help page and  
>> *also* the links from that page to the help pages for locfit.raw  
>> and rv. I would have thought that since family= is not an argument  
>> to locfit per se, but rather is documented in locfit.raw that you  
>> have yet done so, but perhaps not?
>
> I did read the help pages for locfit.raw, and found:
>
> "Local likelihood family; "gaussian"; "binomial"; "poisson"; "gamma"  
> and "geom". Density and rate estimation families are "dens", "rate"  
> and "hazard" (hazard rate). If the family is preceded by a 'q' (for  
> example, family="qbinomial"), quasi-likelihood variance estimates  
> are used. Otherwise, the residual variance (rv) is fixed at 1. The  
> default family is "qgauss" if a response y is provided; "density" if  
> no response is provided. "
>
> However, since the fake data were generated from a known gaussian  
> distribution, I did not imagine that using family=gaussian would  
> lead to such wildly different results. This is what I was hoping to  
> understand, without having to struggle with Catherine's Loader book  
> in order to understand the above paragraph deeply enough that this  
> behavior makes sense.
>
> Thanks again, Suresh
>
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