similar to: issues with calling predict.coxph.penal (survival) inside a function

Full_Name: Yasuhiro Nakajima Version: 2.6.1 OS: WinXP SP2 Submission from: (NULL) (202.237.255.13) Dear all, I noticed the following behaviour of ci.plot in HH Package(ver.2.1-9): > library(HH) > data(women, package="datasets") > attach(women) > ft <- lm(height~weight) > windows() > ci.plot(ft,conf.level=0.95) > windows() > ci.plot(ft,conf.level=0.999) I

The data set in R is wrong. I've found mistakes on 2 lines in a quick look. I don't know if the data is incorrect in the Appendix of Fleming and Harrington as well (someone seems to have borrowed my copy), which is where the data set appears to have been taken from, given all the "-9" codes in it. (Note, Tom Fleming originally got the data from me, so I'm fairly

Hi, There is something I don't get with object of class "mle" returned by a function I wrote. More precisely it's about the behaviour of method "confint" and "profile" applied to these object. I've written a short function (see below) whose arguments are: 1) A univariate sample (arising from a gamma, log-normal or whatever). 2) A character string

Dear R-users; I'm working with a a dataset that was previously used to fit a nonlinear model of the form: Y ~ a * (1 + b * log(1 - c * X^d)) The parameters published elsewhere are: a = 1.758863, b = .217217, c = .99031, and d = .054589 However, there is no way I can replicate this result. I've tried several options (including SAS) w/o success. The data is: X <-

I am working on a script that takes numeric performance indicators and runs them against a series of regressors (dummy regressors, yes\no stuff via 0 and 1, e.g. Was is Christmas this week 0=no, 1=yes). The script is as follows (Written as a function): -- Begin Script -- doEnv <- function(HOUR,ENVNAME,REPORTNAME) { library(RODBC) library(forecast) library("geneplotter")

Dear friends, Sorry for this somewhat generically titled posting but I had a question with using contrasts in a manova context. So here is my question: Suppose I am interested in doing inference on \beta in the case of the model given by: Y = X %*% \beta + e where Y is a n x p matrix of observations, X is a n x m design matrix, \beta is m x p matrix of parameters, and e is a

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)

Hi thank you for talking the time to help me with this. I have a sequence of numbers in a file and an equal sequence of various character, say(a b c d) each occurs more than once. I need to plot the numbers so that numbers corresponding to a in the other sequence would have green dots, those corresponding to b a red dot, nothing on c and blue square for d. i.e 2 a show a green dot 4 b show a

I am writing a program in which I would like to take in a formula, change the response (Y) variable into something else, and then pass the formula, with the new Y variable to another function. That is, I am starting with formula <- Y~X1+X2+X3 and I'd like to do something like Y <- formula$Y newY <- f(Y) lm(newY~X1+X2+X3) So far, it seems that my

Dear R- helpers Following a draft structure of the R script for which I am facing problem Step 1 x <- of type array with original values y <- of type array with original values Step 2 for (ctr in 1:10) { # my problem here the both x and y still show the original values from step 1 # in spite of making changes to the old values of the arrays x and y in the function function

Hi, I am trying to simulate animal movement in a gridded landscape made up of cells. At each time step (iteration), the animal moves from one cell to another in a random fashion. This is how I am simulating movement, where a and b are the x,y co-ordinates of the animal at the previous time step: for (i in 1:no.of.steps){ direction <- sample(1:8, 1) if(direction == 1){ a <- a b <- b -

Dear all, As you can see from the attachment I'm using R to automatically annotate peptide fragmentation mass spectra, which are represented by impulse plots. I'd like to poll you on approaches of how to deal as generally as possible with the two biggest annotation issues I run into: 1) very close annotated masses (impulses) with similar y-axis dimensions - resulting in overlapping labels

Dear R users I need to auto scale the left y axis in the code below, so that when I scroll left or right the left y-axis scale changes to accumulate the range of the displayed data with in the max hight of the y-axis. also how can I make the crosshair horizontal since it is only vertical in this code. this code with a kind help from "Gregory (Greg) L. Snow Ph.D." just

Hi, I would like to step-through a non-visible function. but apparently I don't know enough about namespaces to get that to work: > methods(predict) ... deleted lines ... [27] predict.rpart* predict.smooth.spline* [31] predict.survreg.penal* Non-visible functions are asterisked > debug(predict.rpart) Error: Object "predict.rpart" not found >

A multinomial logit model can be specified as a conditional logit model after restructuring the data. Doing so gives flexibility in imposing restrictions on the dependent variable. One application is to specify a loglinear model for square tables, e.g. quasi-symmetry or quasi-independence, as a multinomial logit model with covariates. Further details on this technique and examples with several

Hi, I'm having a bit of trouble with the axes in my plots. I don't like the way R does not have them cross in the origin. Is there another plot/axis function? i tried using abline as suggested by someone from this list, but in my case this gives no satisfactory result, as the abline does sometimes lie on top of the y axis and sometimes not, depending on how i scale the image... #bild16

Dear All, I'd like to know if it is possible to create animations with R. To be specific, I attach a code I am using for my research to plot some analytical results in 3D using the lattice package. It is not necessary to go through the code. Simply, it plots some 3D density profiles at two different times selected by the user. I wonder if it is possible to use the data generated for different

Colleagues, I am using "nls" successfully (2.11.1, OS X) but I am having difficulties retrieving part of the output - residual sum of squares. I have assigned the output to FIT: > > FIT > Nonlinear regression model > model: NEWY ~ PMESOR + PAMPLITUDE * cos(2 * pi * (NEWX - POFFSET)/PERIOD) > data: parent.frame() > PMESOR PAMPLITUDE POFFSET >

Hello, I have a question regarding shading regions under curves to display 95% confidence intervals. I generated bootstrap results for the slope and intercept of a simple linear regression model using the following code (borrowed from JJ Faraway 2005): > attach(allposs.nine.d) > x<-model.matrix(~log(d.dist,10))[,-1] > bcoef<-matrix(0,1000,2) > for(i in 1:1000){ +

Good afternoon, Hope you all have a wonderful day. I am glad to be here. Hope you could help me with the following errors that i have been trying to figure it all out since last week. I am using Splus from Insightful, and as i read, R and Splus are very similar. So hope you could help me. I have been continously received these error messages after i ran my small program for couple of