[R] loess function take

Bert Gunter gunter.berton at gene.com
Fri Apr 13 16:07:27 CEST 2012


Since you have only one dependent variable, try using lowess()
instead. It is less flexible -- only does local linear robust fitting
-- but has arguments built in that allow you to sample and interpolate
and limit the number of robustness iterations. It runs considerably
faster as a result.

-- Bert

On Fri, Apr 13, 2012 at 6:32 AM, Liaw, Andy <andy_liaw at merck.com> wrote:
> Alternatively, use only a subset to run loess(), either a random sample or something like every other k-th (sorted) data value, or the quantiles.  It's hard for me to imagine that that many data points are going to improve your model much at all (unless you use tiny span).
>
> Andy
>
>
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Uwe Ligges
>
> On 12.04.2012 05:49, arunkumar1111 wrote:
>> Hi
>>
>> The function loess takes very long time if the dataset is very huge
>> I have around 1000000 records
>> and used only one independent variable. still it takes very long time
>>
>> Any suggestion to reduce the time
>
>
> Use another method that is computationally less expensive for that many
> observations.
>
> Uwe Ligges
>
>
>> -----
>> Thanks in Advance
>>          Arun
>> --
>> View this message in context: http://r.789695.n4.nabble.com/loess-function-take-tp4550896p4550896.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
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>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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