MASS fitdistr with plyr or data.table?

Hi:

Here's one way to do this with plyr and data.table.

# plyr
As Hadley inferred, when using ddply(), it's convenient to write a
function for a generic (sub-)data frame and have it return a data
frame. Here's my function and call:

f <- function(d) {
     require(MASS)
     est <- fitdistr(d$wind_speed, 'weibull')$estimate
     data.frame(shape = est[1], scale = est[2])
  }

Notice that f() takes a data frame d as input, uses the wind_speed
component of d to fit the Weibull, and returns a data frame with names
for the estimates.

ddply(weib.test.too, 'site', f)

site    shape    scale
1     1 3.063853 8.049467
2     2 2.945982 8.067252
3     3 2.879392 7.999636
4     4 3.097191 8.084453
5     5 3.091117 8.012450
6     6 2.943254 7.912792
7     7 2.957455 7.947545
8     8 2.975732 7.901587
9     9 3.045563 8.061838
10   10 2.995324 8.056820
Warning messages:
1: In dweibull(x, shape, scale, log) : NaNs produced
2: In dweibull(x, shape, scale, log) : NaNs produced
<snip the other eight>

## data.table

In writing a function for data.table, you want a variable as input and
a list as output. We therefore modify the above function slightly:

g <- function(x) {
     require(MASS)
     est <- fitdistr(x, 'weibull')$estimate
     list(shape = est[1], scale = est[2])
  }

library(data.table)
weib.test.dt <- data.table(weib.test.too, key = 'site')

weib.test.dt[, g(wind_speed), by = site]

site    shape    scale
 [1,]    1 3.063853 8.049467
 [2,]    2 2.945982 8.067252
 [3,]    3 2.879392 7.999636
 [4,]    4 3.097191 8.084453
 [5,]    5 3.091117 8.012450
 [6,]    6 2.943254 7.912792
 [7,]    7 2.957455 7.947545
 [8,]    8 2.975732 7.901587
 [9,]    9 3.045563 8.061838
[10,]   10 2.995324 8.056820
## <warnings snipped>

HTH,
Dennis

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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