Hi Justin,
One way of doing it is using a combination of tapply() and sapply() as
follows:
# data
set.seed(144)
weib.dist<-rweibull(10000,shape=3,scale=8)
weib.test.too<-data.frame(cbind(1:10,weib.dist))
names(weib.test.too)<-c('site','wind_speed')
# results
require(MASS)
out <- with(weib.test.too, tapply(wind_speed, site, function(x) fitdistr(x,
'weibull')))
estimates <- t(sapply(out, "[[", 1))
SDs <- t(sapply(out, "[[", 2))
estimates
SDs
HTH,
Jorge
On Wed, Apr 27, 2011 at 4:55 PM, Justin Haynes <> wrote:
> I am trying to extract the shape and scale parameters of a wind speed
> distribution for different sites. I can do this in a clunky way, but
> I was hoping to find a way using data.table or plyr. However, when I
> try I am met with the following:
>
> set.seed(144)
> weib.dist<-rweibull(10000,shape=3,scale=8)
> weib.test<-data.table(cbind(1:10,weib.dist))
> names(weib.test)<-c('site','wind_speed')
>
> fitted<-weib.test[,fitdistr(wind_speed,'weibull'),by=site]
>
> Error in class(ans[[length(byval) + jj]]) = class(testj[[jj]]) :
> invalid to set the class to matrix unless the dimension attribute is
> of length 2 (was 0)
> In addition: Warning messages:
> 1: In dweibull(x, shape, scale, log) : NaNs produced
> ...
> 10: In dweibull(x, shape, scale, log) : NaNs produced
>
> (the warning messages are normal from what I can tell)
>
> or using plyr:
>
> set.seed(144)
> weib.dist<-rweibull(10000,shape=3,scale=8)
> weib.test.too<-data.frame(cbind(1:10,weib.dist))
> names(weib.test.too)<-c('site','wind_speed')
>
> fitted<-ddply(weib.test.too,.(site),fitdistr,'weibull')
>
> Error in .fun(piece, ...) : 'x' must be a non-empty numeric vector
>
> those sound like similar errors to me, but I can't figure out how to
> make them go away!
>
> to prove I'm not crazy:
>
> fitdistr(weib.dist,'weibull')$estimate
> shape scale
> 2.996815 8.009757
> Warning messages:
> 1: In dweibull(x, shape, scale, log) : NaNs produced
> 2: In dweibull(x, shape, scale, log) : NaNs produced
> 3: In dweibull(x, shape, scale, log) : NaNs produced
> 4: In dweibull(x, shape, scale, log) : NaNs produced
>
> Thanks
>
> Justin
>
> ______________________________________________
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> PLEASE do read the posting guide
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>
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