If you know the knot and want linear segments, lm (or any other "normal"
regression software) can perform the analysis. For example if you want to
regress y on x and have a knot a 20 the following code will work:
x <- runif(500,0,40)
plot(x)
for (i in 1:500) {
if (x[i] < 20) y[i] <- (-0.5*x[i])+rnorm(1)
if (x[i] >= 20) y[i] <- ( 0.5*x[i])+rnorm(1) -20
}
plot(x,y)
knot <- 20
aboveknot <- pmax(x-knot,rep(0,500))# will be 0 for x < 20, x for x >20
fit1 <- lm(y~x+aboveknot)
summary(fit1)
The analysis will give you three parameters
(1) the intercept
(2) the slope of below 20
(3) the difference between the slope below 20 and above 20
John
John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
Baltimore VA Medical Center GRECC,
University of Maryland School of Medicine Claude D. Pepper OAIC,
University of Maryland Clinical Nutrition Research Unit, and
Baltimore VA Center Stroke of Excellence
University of Maryland School of Medicine
Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
jsorkin at grecc.umaryland.edu
Gene Leynes <gleynes+r at gmail.com> 1/14/2011 11:50 AM >>>
oh yes, and the structchange package.
After a day of experimentation I couldn't figure out how to get the
structchange package to work for my problems. Although it is probably user
error on my part, the package seems to be specific to time series problems.
Also, I think it needed regularly spaced x's... but maybe that would be a
good thing to look at as part of a two step approach (smoothing first to get
regularly spaced data).
PS: Actually, I just noticed that there are some other help topics that I
had not read yet which went up last November.
http://r-project.markmail.org/thread/npjhlwwt6oh3sby3
On Fri, Jan 14, 2011 at 10:25 AM, Spencer Graves <
spencer.graves at structuremonitoring.com> wrote:
Hello:
I just found 58 help pages in 32 contributed packages containing the
terms "piecewise" and "regression", as follows:
library(sos)
pr <- ???'piecewise regression' # for "piecewise" with "regression"
summary(pr) # 58 matches in 32 packages
pr # view the 58 links sorted by package in a web browser
p.r <- ???"{piecewise regression}" # for "piecewise" followed immediate by
"regression"
summary(p.r) # 15 matches in 13 packages
p.4 # to view in a web browser
Beyond this, the "structchange" package supports looking for changes
that would be, e.g., linear in one segment then jump to a different linear
regime. If you want the lines to connect, then you may want splines.
Probably the most common spline is cubic, but you can also get linear
splines. One of the most general spline packages is "fda" (functional data
analysis), with multiple companion books by James Ramsay and others.
However, there are other spline packages.
If this does not answer your question, "PLEASE do read the posting
guide http://www.R-project.org/posting-guide.html and provide commented,
minimal, self-contained, reproducible code", as it says in the signature
block for each email on this list.
Hope this helps.
Spencer Graves
On 1/14/2011 6:42 AM, Federico Bonofiglio wrote:
Hello everybody!!!!
Quick question, if you'd like to throw a little tip:
does anyone knows a function that runs piecewise regression models with
coefficients estimation and inferences ?
Thank you
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