similar to: terms.formula

Suppose I have a formula like this: f <- y ~ qss(x, lambda = lambdas[1]) + qss(z, lambdas[2]) + s I?d like a function, g(lambdas, f) that would take g(c(2,3), f) and produce the new formula: y ~ qss(x, lambda = 2) + qss(z, 3) + s For only two qss terms I have been using g <- function(lambdas, f){ F <- deparse(f) F <- gsub("lambdas\\[1\\]",lambdas[1],F) F

Recursively walk the formula performing the replacement: g <- function(e, ...) { if (length(e) > 1) { if (identical(e[[2]], as.name(names(list(...))))) { e <- eval(e, list(...)) } if (length(e) > 1) for (i in 1:length(e)) e[[i]] <- Recall(e[[i]], ...) } e } g(f, lambdas = 2:3) ## y ~ qss(x, lambda = 2L) + qss(z, 3L) + s On Fri, Oct

I'm having difficulty with an environmental issue: I have an additive model fitting function with a typical call that looks like this: require(quantreg) n <- 100 x <- runif(n,0,10) y <- sin(x) + rnorm(n)/5 d <- data.frame(x,y) lam <- 2 f <- rqss(y ~ qss(x, lambda = lam), data = d) this is fine when invoked as is; x and y are found in d, and lam is found the

While installing my small package, I met a tricky problem. For clarity, let me explain it with the following simplified example. In ~/pkg/R/aclass.R, setClass("aclass", contains="bclass", representation(i="numeric")) In ~/pkg/R/bclass.R, setClass("bclass", representation(j="numeric")) After building a "pkg" package, the file

I'd like to mention that there is a new quantile regression package "nprq" on CRAN for additive nonparametric quantile regression estimation. Models are structured similarly to the gss package of Gu and the mgcv package of Wood. Formulae like y ~ qss(z1) + qss(z2) + X are interpreted as a partially linear model in the covariates of X, with nonparametric components defined as

About 2 percent of the time I use fix() to edit a function that is sitting in .RData I get the response: > fix(qss) Error in edit(name, file, editor) : problem with running editor vi when I try to close the editing session. I used to think that these were always cases where there was some syntactical error with the edited file, but this is not the case. I realize that one surefire way to

Hello, i have the following data: x=c(0,0.02,0.03,0.04,0.05,0.06,0.07,0.08,0.09,0.1,0.11,0.12,0.13,0.14,0.15,0.16,0.17,0.18,0.19,0.2,0.21,0.22,0.23,0.25,0.26,0.27,0.46,0.47,0.48,0.49) y=c(0.48,0.46,0.41,0.36,0.32,0.35,0.48,0.47,0.55,0.56,0.54,0.67,0.61,0.60,0.54,0.51,0.45,0.42,0.44,0.46,0.41,0.43,0.43,0.48,0.48,0.47,0.39,0.37,0.32,0.29) and tried to get piecewise linear regression. Doing a

Hi, I have used package quantreg to estimate a non-linear fit to the lowest part of my data points. It works great, by the way. But I'd like to extract the predicted values. The help for predict.qss1 indicates this: predict.qss1(object, newdata, ...) and states that newdata is a data frame describing the observations at which prediction is to be made. I used the same technique I used

Rers: I installed R 2.9.0 from the Debian package manager on our amd64 system that currently has 6GB of RAM -- my first question is whether this installation is a true 64-bit installation (should R have access to > 4GB of RAM?) I suspect so, because I was running an rqss() (package quantreg, installed via install.packages() -- I noticed it required a compilation of the source) and

Hello, I am using R 1.7.1 on a Redhat Linux machine, version 7.3. The following works fine: setClass("ok", representation( "A" = "matrix", "Cmatrix" = "matrix")) new("ok", "A" = diag(4), "Cmatrix" = diag(4)) But the following doesn't work: setClass("notok", representation(

"C" appears to be an illegal name for a slot in an S4 class (example below). If this is a known limitation, and not a bug, it would be nice if it were caught by setClass. Paul Gilbert > setClass("testobj", representation ( C = "numeric")) [1] "testobj" > new("testobj", C= 2) Error in methodsPackageMetaName("C", name) :

I am using the latest version of R on a Windows machine and get the following error when I try to initialize a correlation structure with the function corAR1 in NLME. This example is taken from the book of Pinheiro and Bates, so it should work. What is going wrong? > library(nlme) > data(Orthodont) > cs1AR1 <- corAR1(0.8, form= ~1 | Subject) > cs1AR1 <- initialize(cs1AR1, data =

Dear all, My machine is SUN Java Workstation 2100 with 2 AMD Opteron CPUs and 16GB RAM. R is compiled as 64bit by using SUN compilers. I trying to fit quantile smoothing on my data and I got an message as below. > fit1<-rqss(z1~qss(cbind(x,y),lambda=la1),tau=t1) Error in as.matrix.csr(diag(n)) : cannot allocate memory block of size 2496135168 The lengths of vector x and y are

I'm trying to create a formula object to pass on to a function that applies the function terms.formula() to it. f <- function(formula, ...) { ... mf <- match.call() term <- terms.formula(mf$formula) ... } However, my code below gives an error. form <- as.formula("y~x") f(form, ...) The error message was: Error in terms.formula(mf$formula): argument is not a valid

Gurus: I have a new version of my quantreg package with minimal changes, mainly to fix some obscure fortran problems. It fails R CMD check ?as-cran with the error: Running examples in ?quantreg-Ex.R? failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: plot.rqss > ### Title: Plot Method for rqss Objects

Dear All, I'm trying to construct confidence interval for an additive quantile regression model. In the quantreg package, vignettes section: Additive Models for Conditional Quantiles http://cran.r-project.org/web/packages/quantreg/index.html It describes how to construct the intervals, it gives the covariance matrix for the full set of parameters, \theta is given by the sandwich formula

Hi, Let me pick up this old thread. How does one extract the locations of the knots (ends of the segments) from the fit object below? Thanks, Vadim >From : roger koenker < roger_at_ysidro.econ.uiuc.edu > Date : Tue 31 May 2005 - 10:23:19 EST It is conventional to fit piecewise linear models by assuming Gaussian error and using least squares methods, but one can argue that

I am new to R. I'm using the function GAM and wanted to get standard errors and p-values for the parametric terms (I fitted a semi-parametric models). Using the function anova() on the object from GAM, I only get p-values for the nonparametric terms. Does anyone know if and how to get standard errors for the parametric terms? Thanks. Jean G. Orelien

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 \ \ /\

Full_Name: simon wood Version: 2.2.0 (and lower) OS: linux/windows Submission from: (NULL) (86.135.153.59) I think that the documentation for the `specials' attribute of a `terms.object' is not quite right: specials: If the 'specials' argument was given to 'terms.formula' there is a 'specials' attribute, a list of vectors indicating the terms