similar to: Simple question regarding domain restrictions/piecewise functions in R

Hi, I am a biologist (relatively new to R) analyzing data which we predict to fit a power function. I was wondering if anyone knew a way to model piecewise functions in R, where across a range of values (0-x) the data is modeled as a power function, and across another range (x-inf) it is a linear function. This would be predicted by one of our hypotheses, and we would like to find the AICs

Hi R experts, I'm trying to use nls() for a piecewise linear regression with the first slope constrained to 0. There are 10 data points and when it does converge the second slope is almost always over estimated for some reason. I have many sets of these 10-point datasets that I need to do. The following segment of code is an example, and sorry for the overly precise numbers, they are just

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

I am looking into fitting a so-called double von Bertalanffy function to fish length-at-age data. Attempting to simplify the situation, the model looks like this ... Y ~ f(X; a,b,c) if x < Z Y ~ g(X; a,d,e) if x >= Z where * f and g are non-linear functions (the "traditional" "single" von Bertalanffy growth function), * Y (length) and X (age) are observed variables,

Dear all, I am just wondering if anybody has implemented a function that can give a piecewise linear interpolation in more than 2 dimensions? I have looked at the akima package, but I would rather like a piecewise linear interpolation rather than a spline and while it did the job quite satisfactory for 2 dimensions, I need to interpolate in at least three dimensions. If anybody has implemented

Which function implements the piecewise cubic Hermite interpolation? I am looking for equivalent of matlab's interp1 with the method = 'pchip' Here is the reference http://www.mathworks.com/access/helpdesk/help/techdoc/index.html?/access/helpdesk/help/techdoc/ref/interp1.html& -- View this message in context:

Hi All, I am trying to fit a piecewise lasso regression, but package Segmented does not work with Lars objects. Does any know of any package or implementation of piecewise lasso regression? Thanks, Lucas

Hi, I need to fit a piecewise linear regression. x = c(6.25,6.25,12.50,12.50,18.75,25.00,25.00,25.00,31.25,31.25,37.50,37.50,50.00,50.00,62.50,62.50,75.00,75.00,75.00,100.00,100.00) y = c(0.328,0.395,0.321,0.239,0.282,0.230,0.273,0.347,0.211,0.210,0.259,0.186,0.301,0.270,0.252,0.247,0.277,0.229,0.225,0.168,0.202) there are two change points. so the fitted curve should look like \ \ /\

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 [[alternative HTML version deleted]]

Hi all, I'm a relatively new user to the R interface, and am trying to do some basic operations. So far I've used the curve() command to plot graphs. This has a couple of limitations, namely trying to do piecewise graphs. Basically, I'm looking for how to do "if" and "while" loops for making a graph. in simple code, something like: if x is on the interval [-1,1],

dear all, I apologize for my delay in replying you. Here my contribution, maybe just for completeness: Similar to "earth", "segmented" also fits piecewise linear relationships with the number of breakpoints being selected by the AIC or BIC (recommended). #code (example and code from Martin Maechler previous email) library(segmented) o<-selgmented(y, ~x, Kmax=20,

Dear all, I have two variables, y and x. It seems that the relationship between them is Piecewise Linear Functions. The cutpoint is 20. That is, when x<20, there is a linear relationship between y and x; while x>=20, there is another different linear relationship between them. How can i specify their relationships in R correctly? # glm(y~I(x<20)+I(x>=20),family = binomial, data =

Dear Rusers, I am now using R and SAS to fit the piecewise linear functions, and what surprised me is that they have a great differrent result. See below. #R code--Knots for distance are 16.13 and 24, respectively, and Knots for y are -0.4357 and -0.3202 m.glm<-glm(mark~x+poly(elevation,2)+bs(distance,degree=1,knots=c(16.13,24)) +bs(y,degree=1,knots=c(-0.4357,-0.3202

How can I fit a piecewise continuous logistic regression with a single free knot (i.e. the knot is not specified; the model produce an estimate of the value of the knot). Thank you, John John David Sorkin M.D., Ph.D. Professor of Medicine Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine Baltimore VA Medical Center

Dear all, I want to do piecewise CAPM linear regression in R: RRiskArb−Rf = (1−δ)[αMktLow+βMktLow(RMkt−Rf)] + δ[αMkt High +βMkt High(RMkt −Rf )] where δ is a dummy variable if the excess return on the value-weighted CRSP index is above a threshold level and zero otherwise. and at the same time add the restriction: αMkt Low + βMkt Low · Threshold = αMkt High + βMkt High · Threshold to ensure

Hi All, I want to fit a piecewise spline of degree 1, i.e. a spline consisting of a straight line over each piece. I downloaded the R package pspline, then I have following questions: 1. in the program, the degree of the spline is specified by 2*norder-1. Why do they adopt such scheme that we can only fit a spline with odd degree? 2. norder cannot be set to 1. Is there any specific reason

How can I do automatic knot selection while fitting piecewise linear splines to two variables x and y? Which package to use to do it simply? I also want to visualize the splines (and the scatter plot) with a graph. Anupam [[alternative HTML version deleted]]

>>>>> Anupam Tyagi >>>>> on Tue, 9 Jul 2024 16:16:43 +0530 writes: > How can I do automatic knot selection while fitting piecewise linear > splines to two variables x and y? Which package to use to do it simply? I > also want to visualize the splines (and the scatter plot) with a graph. > Anupam NB: linear splines, i.e. piecewise

Hello, Fitting a piecewise smooth curve to a set of points (and a piecewise linear function in particular) seems to be a recurring question on this list. Nevertheless, I was not able to find an answer to a question that bothers me. Suppose I have the following data set, and would want to fit it with a piecewise smooth curve, In this model data, one curve is valid for up to 3 and another one for

Dear R-helpers, a S-code for piecewise regressions was provided by Toms & Lesperance (2003) Ecology, 84, 2034-2041 (paper can be found on the web).The code is quite complete with different types of transitions around breakpoints and model selection fonctions. It doesn't work directly under R due to some "translation" problems I guess. However I reckon that it would be a