similar to: isotonic regression

Hi All, I have a four panel xyplot. I wish to plot each point as an open or filled circle depending on the value of an indicator variable. I assume I need to use panel.superpose(), but I can't figure out the syntax from lattice documentation. Running R 2.1 under Mac OS X 10.4.2. Any suggestions would be appreciated. Nathan Nathan Leon Pace, MD, MStat University of Utah Salt Lake

Hi, I using the boot package 1.2-20 on R 2.0.1. My statistics function estimates 6 parameters. In a small percentage of resampled data sets my statistics function doesn't produce an estimate for one parameter and the boot function stops with an error. I can write an ifelse(exists('parameter.estimate'), parameter.estimate, NA) statement within the statistic function to substitute

In the non linear mixed effects package a groupedData object can be created to facilitate modeling. The gD object includes a formula of the form 'response variable' ~ 'primary covariate' | 'grouping factor'. In experiments creating response surfaces there are 2 or more primary covariates. Is there any way to use the groupedData() function to include 2 primary

Running under Redhat 7.3 Linux I have installed R Version 1.8.0 (2003-10-08) from a binary download using the rpm manager. Using packageStatus(), I am attempted to upgrade several packages. This is unsuccessful with the following error messages: * Installing *source* package 'MASS' ... ** libs gcc -I/usr/lib/R/include -I/usr/local/include -D__NO_MATH_INLINES -mieee-fp -fPIC -O2

To all: I currently download the R binaries for Redhat 7.x Linux. There is considerable turmoil in the vendors of Linux. Redhat apparently is changing it's business model to paid versions. This might motivate my department to use a different vendor of Linux. Is there anything predictable about which vendors/versions of Linux will have R binaries in the future? Thanks, Nathan PS I

Hi All, I'm new at programming in R. Some functions create objects for which extractor functions are written to pull out some partial result. I wish to extract partial results from functions without extractor functions: for example, to pass a vector of results to another function. Even after looking at V&R S Programming I don't see a general approach. Specifically, how would I

> Hello, > > I'm running R 1.8.1 on a Mac G4 with Dual 800 MHz CPU, 1.5 GB RAM, and > sufficient disk space. > > I have loaded the boot package version 1.2-15. > > I defined a function to pass to the statistic argument which estimates > a vector (length = 6) of parameter estimates; none are variances. > > I defined a function to pass to the ran.gen argument

Well, I could argue that it's not *completely* OT since my question is motivated by an enquiry that I received in respect of a CRAN package "Iso" that I wrote and maintain. The question is this: Given observations y_1, ..., y_n, what is the solution to the problem: minimise \sum_{i=1}^n (y_i - y_i^*)^2 with respect to y_1^*, ..., y_n^* subject to the "isotonic"

This is a question of clarification. IN 2009 Higgins, Thompson and Spiegelhalter (J R Statist Soc A 172:137-159) gave WinBUGs code to get credible intervals from random effects meta analysis for the prediction interval of a new study. It appears that the predict.rma function creates approximate credible intervals (pending a function revision by the author) for that purpose. Is my assumption

dear R-help: one of my students is struggling to test an ordered alternative hypothesis on a set of groups (e.g., mu_a <= mu_b <= mu_c). There has been some literature on this topic -- a lot of this goes back to Bartholomew (1961); Gaines and Rice (see refs below) are the ones who've popularized it in the ecology community. The topic is closely related to isotonic regression, but

Dear R-users Do you know of an easy way in R of performing "isotonic (unimodal)" regression ala BBBB, Barlow, Bartolomew, Brenner and Brunk. best regards Helgi -- Helgi Tomasson FAX: 354-552-6806 University of Iceland PHONE:354-525-4571 Faculty of Economics and Business Administration email:helgito at

Hi, I've got a linear mixed model created using lmer: A6mlm <- lmer(Score ~ division + (1|school), data=Age6m) (To those of you to whom this model looks familiar, thanks for your patience with this & my other questions.) Anyway, I was trying this to look at the significance of my fixed effects: A6post <- mcmcsamp(A6mlm, 50000) library(coda) HPDinterval(A6post) ..but I got this

Hi, I was wondering: I've got a dataset where I've got student 'project's nested within 'school's, and 'division' (elementary, junior, or senior) at the student project level. (Division is at the student level and not nested within schools because some students are registered as juniors & others as seniors within the same school.) So schools are random,

Before re-inventing the wheel I would like to ask: does anyone know about an optimizer in R which can reliably identify which value of X (Xopt) leads to Y (Yopt) closest to Ytarget in Y <- MonotoneStepFun(X) optionally with the restriction that Yopt <= Ytarget (at least if any Y <= Ytarget, otherwise any Yopt > Ytarget would be the preferred answer) If none is known, I will write

Dear Friends, I'm trying to learn to use parallel computation using snow & rpvm Now, I have two boxes: 1) Pentium 4, pvm 3.4.5, R 2.2.0 with FreeBSD 5.4 (box uffbsd); 2) PowerPC, pvm 3.4.5, R 2.1.1 with Debian Linux latest stable (box powerpclinux); I'm using the instructions in (found in snow.pdf) http://www.stat.uiowa. edu/~luke/R/cluster/cluster.html. Now ** from the box

I have a function (see below) that does some bootstrapping (I am happy to expand offline why I could use existing functions.) I put my results into and empty matrix and add a row of results with each iteration. My problem is i am a new user to R and I don't understand data frames, matrices, elements, and vectors well. What I would like is to have a data frame I can manipulate outside of the

Dear Sir/Madam: this is shuangge Ma, graduate student in UW-Madison statistics department. I have a computational question. I have a function f(x,y). I want to find the y(x) that maximize f(x,y) under the constraint y(x) is a non-decreasing step function. Is there any R package or algorithm I can use for this purpose? thanks a lot for your time and help, Sincerely, Shuangge Ma

Dear All, A method for the estimation is univariate unimodal densities (with unknown mode) is described in "Statistical Inference under Order Restrictions" by Barlow et al.. Would anyone know whether there is an R-implementation (preferably with reference) for the estimation of univariate discrete unimodal densities (with unknown mode)? Thanks in advance for your help. Kind

I am running R 2.1.1 on a Mac g5 under Mac OS 10.4.2. I have an xyplot with a single conditioning variable (8 levels) . Here is the code for the conditioning variable used in the formula argument of xyplot: factor( drugauthoryear, levels = c( 'bupicapogna1999', 'levobenhamou2003', 'ropicapogna1999',

Hi all, I'm looking for smooth monotone estimation packages, preferably using splines. I downloaded the 'cobs' package and intend to use it, but since it offers only quadratic splines based on L1 minimization, I'd like to compare its performance to that of a more 'mainstream' cubic-spline, L2-norm minimizing spline. Preferably a smoothing spline. Does anyone know of such