On 2010-12-23 2:19, David Bapst wrote:
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
Hi,
you may try the following code:
> library(triangle)
> library(fitdistrplus)
> summary(fitdist(y, "triangle", start = list(a = 1.9, b= 21.1, c = 11.5)))
Fitting of the distribution ' triangle ' by maximum likelihood
Parameters :
estimate Std. Error
a -1.400007 2.3523724
b 23.627448 1.9804026
c 13.000000 0.1107073
Loglikelihood: -62.41994 AIC: 130.8399 BIC: 133.8271
Correlation matrix:
a b c
a 1.00000000 -0.14537297 -0.01203898
b -0.14537297 1.00000000 -0.01439500
c -0.01203898 -0.01439500 1.00000000
HTH ...
Jinsong Zhao
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