similar to: fix(fix)

I'm in the very initial stage of expanding the formula processing in my quantile regression function rq() to handle additive nonparametric components, say qss(x), or qss(x,z). I need some advice about strategy for formula processing. My initial foray was to use: terms(formula,specials="qss") and then modify the components of the resulting terms.object. But in changing formula

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

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've had a play with this and, due to my own short-comings, remain none the wiser. In particular, I'm not sure what value of 'spar' is consistent with the magic lambda=1/1600 for quarterly data. I initially interpreted spar as lambda and tried setting spar=1/1600. This results in almost no smoothing while spar=1600 causes an error. The smooth.spline function seems to want

I've been playing with a quincunx animation in R 1.2.2 and would like to have finer control over the speed of the animation. I know that I can use system("sleep 1") on unix systems at least, but it would be nice to have something like pause(.01). Any suggestions? url: http://www.econ.uiuc.edu Roger Koenker email roger at ysidro.econ.uiuc.edu Department of Economics vox:

In ancient times, circa 1980, S data directories were called swork and sdata not .Data, and "New-S" as described in the already medieval "Blue Book" discusses a function DBCONVERT that converted swork data into .Data data. It is embarrassing to admit it, but I still have data archives from a BTL machine called alice in the swork format and would like to convert a dataset to

We've recently "upgraded" a server to solaris 8, and in reinstalling R I've encountered a problem in getting it to recognize the readline library. I have installed readline in what I believe to be the "usual" place: /usr/local/lib with include files in /usr/local/include/readline. But ./configure produces: ragnar.econ.uiuc.edu# grep readline hout checking for

I am trying to make R-1.5.0 from source on a new G4 system with the apple developer tools and X11 installed and with ATLAS. Running ./configure appears to end normally, but running make yields: gcc -no-cpp-precomp -I. -I../../src/include -I../../src/include -I/usr/local/include -DHAVE_CONFIG_H -g -O2 -c Rdynload.c -o Rdynload.o Rdynload.c: In function `R_FindSymbol': Rdynload.c:942:

In the time honored spirit of wishing to do nothing well, could I suggest that the Splus (versions 5 and 6) response to: > rbind(NULL,NULL) NULL is preferable to the R response: > rbind(NULL,NULL) Error in rbind(NULL, NULL) : attempt to set an attribute on NULL This is on: platform sparc-sun-solaris2.8 arch sparc os solaris2.8 system sparc, solaris2.8 status major 1

Hi, I have been trying to dyn.load a library (rq.obj), which will allow me to run a quantile regression function, but so far unsuccessfully. I have tried under windows 98 and R 6.24: 1) dyn.load("d:\\...\\rq.obj") 2) dyn.load("d:\...\rq.obj") 3) 1 and 2 accounting for case sensitivity. 4) dyn.load("d:/.../rq.obj") 5) Place the files in the directory where from I

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

We have recently upgraded to Solaris 10 on a couple of sparc machines with the usual mildly mysterious consequences for library locations, etc, etc. I've managed to configure R 2.1.0 for a 64 bit version with: R is now configured for sparc-sun-solaris2.10 Source directory: . Installation directory: /usr/local C compiler: gcc -m64 -g -O2 C++

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

This is an inquiry for all those who have been working on external data base applications. I sent an inquiry (below) to snews about this sort of thing a couple of years ago and eventually decided that I would wait to see what external database developments occurred and then revisit the problem. I hope that foundations are now better. Suppose for the sake of concreteness you have a large

We have a solaris/sparc machine that has been running an old version of R-devel: Version 2.2.0 Under development (unstable) (2005-06-04 r34577) which was built as m64 from sources. Attempting to upgrade to 2.4.0 the configure step goes ok, but I'm getting early on from make: > gcc -m64 -L/opt/sfw/lib/sparcv9 -L/usr/lib/sparcv9 > -L/usr/openwin/lib/sparcv9 -L/usr/local/lib -o

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

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