I don't know if any specific package has a triangular distribution, but I
know you can fit a model using first degree b-splines with a single knot.
library(splines)
?bs
x <- 1:100
y <- rnorm(100, ifelse(x <50, x, 100-x), 15)
fit <- lm(y ~ bs(x, knots = 50, degree = 1))
--------------------------------------
Jonathan P. Daily
Technician - USGS Leetown Science Center
11649 Leetown Road
Kearneysville WV, 25430
(304) 724-4480
"Is the room still a room when its empty? Does the room,
the thing itself have purpose? Or do we, what's the word... imbue it."
- Jubal Early, Firefly
r-help-boun...@r-project.org wrote on 12/22/2010 01:19:16 PM:
> [image removed]
>
> [R] Fitting a Triangular Distribution to Bivariate Data
>
> David Bapst
>
> to:
>
> r-help
>
> 12/22/2010 04:04 PM
>
> Sent by:
>
> r-help-boun...@r-project.org
>
> Hello,
> I have some xy data which clearly shows a non-monotonic, peaked
> triangular trend. You can get an idea of what it looks like with:
>
> x<-1:20
> y<-c(2*x[1:10]+1,-2*x[11:20]+42)
>
> I've tried fitting a quadratic, but it just doesn't the data-structure
> with the break point adequately. Is there anyway to fit a triangular
> or 'tent' function to my data in R?
>
> Some sample code would be appreciated; I'm not new to R, but I
> sometimes have difficulty understanding the model-fitting functions
> (finally figured out how to extrapolate with predict() today!)
>
> Thanks!
> -Dave Bapst, UChicago
>
> ______________________________________________
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