Also note that ifelse() should be avoided as much as possible. To define a
piecewise function you can use this trick:
func <- function (x, min, max) 1/(max-min) * (x >= min & x <= max)
The performances are much better. This has no impact here, but it is a good
habit to take in case you manipulate such kind of functions in a more
computing-intensive context (numerical integration, nls(), etc.).
funcIfElse <- function (x, min, max) ifelse(x < min | x > max, 0, 1/(max - min))
min <- 100; max <- 200; x <- 1:300
microbenchmark::microbenchmark(func(x, min, max), funcIfElse(x, min, max))
## Unit: microseconds
## expr min lq mean median
uq max neval
## func(x, min, max) 10.242 16.0175 18.43348 18.446 19.8680
47.266 100
## funcIfElse(x, min, max) 90.386 125.1605 148.18555 143.455 148.6695 1203.292
100
Best,
Philippe Grosjean
> On 31 Jan 2015, at 09:39, Rolf Turner <r.tur...@auckland.ac.nz> wrote:
>
> On 31/01/15 21:10, C W wrote:
>> Hi Bill,
>>
>> One quick question. What if I wanted to use curve() for a uniform
>> distribution?
>>
>> Say, unif(0.5, 1.3), 0 elsewhere.
>>
>> My R code:
>> func <- function(min, max){
>> 1 / (max - min)
>> }
>>
>> curve(func(min = 0.5, max = 1.3), from = 0, to = 2)
>>
>> curve() wants an expression, but I have a constant. And I want zero
>> everywhere else.
>
> Well if that's what you want, then say so!!!
>
> func <- function(x,min,max) {
> ifelse(x < min | x > max, 0, 1/(max - min))
> }
>
> curve(func(u,0.5,1.3),0,2,xname="u")
>
> Or, better (?) curve(func(u,0.5,1.3),0,2,xname="u",type="s")
>
> which avoids the slight slope in the "vertical" lines.
>
> cheers,
>
> Rolf Turner
>
> --
> Rolf Turner
> Technical Editor ANZJS
> Department of Statistics
> University of Auckland
> Phone: +64-9-373-7599 ext. 88276
> Home phone: +64-9-480-4619
>
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