similar to: "object not found"

Hi all, The problem is that when you try to use the function summary of a polr object in a function, it does not work. The problem is not related to the formula or the structure of data involved. It is probably related to the use of the function "vcov" in the code of summary for polr, and the iterative procedure to estimate the Hessian. Anyway, here there is an example extracted from

Hi all, I have a problem to estimate Std. Error and t-value by ?polr? in library Mass. They result from the summary of a polr object. I can obtain them working in the R environment with the following statements: temp <- polr(formula = formula1, data = data1) coeff <- summary(temp), but when the above statements are enclosed in a function, summary reports the following error:

Dear All, I am trying to use ode solver "rk4" to solve an ODE system, however, it keeps saying: Error in eval(expr, envir, enclos) : object "dIN" not found. The sample codes are enclosed as follows, please help me. Thank you very much! rm(list=ls()) library(odesolve) # The ODE system ode <- function(t,x,p){ with(as.list(c(x,p)),{

Dear All, I am trying to use ode solver "rk4" to solve an ODE system, however, it keeps saying: Error in eval(expr, envir, enclos) : object "dIN" not found. The sample codes are enclosed as follows, please help me. Thank you very much! rm(list=ls()) library(odesolve) # The ODE system ode <- function(t,x,p){ with(as.list(c(x,p)),{

Hi all, I'm having some difficulty passing arguments into lm() from within a function, and I was hoping someone wiser in the ways of R could tell me what I'm doing wrong. I have the following: lmwrap <- function(...) { wts <- somefunction() print(wts) # This works, wts has the values I expect fit <- lm(weights=wts,...) return(fit) } If I call my function lmwrap, I get

Hi R-listers, I am trying to make a trellis boxplot with the HSuccess (y-axis) in each Rayos (beach sections) (x-axis), for each Aeventexhumed (A, B, C) - nesting event. I am not able to do so and keep receiving: Error in eval(expr, envir, enclos) : object 'Rayos' not found Please advise, Jean require(plyr) resp <- read.csv("ABC Arribada R File Dec 12 Jean

> datafilename="E:/my documents/r/sex/bysex1.csv" > data.sex=read.table(datafilename,header=T) > data.sex y.sex.age.region.c.n 1 1980,F,A,N,-18.15,13.61 2 1980,F,A,N,-18.61,13.04 3 1980,F,A,N,-18.81,12.32 4 1990,F,A,N,-21.12,11.7 5 1990,F,A,N,-20.77,11.58 6 1990,F,A,N,-21.6,13.34 7 1990,F,A,N,-21.78,12.6 > model.anova<-aov(c~age*sex,data=data.sex)

Hi! When running the following code I get the message: Error in eval(expr, envir, enclos) : object "A" not found fm <- function(p,ydata, env = parent.frame()) { #fit model y ~ (b0+b1x1+...+bpxp)*exp(g2plus*z2plus) where bi and g2plus are parameters #create design matrix for linear part fo00 <-

This is my first time running GAMs in R. My csv file has these column headings: "X" "Y" "Sound" "Atlantic" "Blacktip" "Bonnet" "Bull" "Finetooth" "Lemon" "Scalloped" "Sandbar" "Spinner" "Abundance" "Diversity"

Hi, I'm trying to fit a ordered logistic regression. The response variable (y) has three levels (0,1,2). The command I've used is: /ordlog<-polr(y~x1+x2+x3+x4, data=finalbase, subset=heard, weight=wt, na.action=na.omit) / (There are no NA's in y but there are NA's in X's) The error I'm getting is: /Warning messages: 1: non-integer #successes in a binomial glm! in:

Hi - I use stepAIC to automatically select the model. The stepAIC was applied on polr as follow:objPolr <- polr(formula=myformula, data=dat, method=METHOD);objPolr.step <- stepAIC(objPolr, trace=T);Then R complaints that it doesn't know about 'dat' when it executes the second line. Below is the exact error that I got when executing the stepAIC line above:Error in eval(expr,

With the incorporation of the useful hints, my user function now looks like this: userfn <- function() { ... ow <- options("warn") options(warn = 2); ... reg<-try(polr(act~.,data=mm,Hess=TRUE)) ... sumreg<-try(summary(reg)) print(length(sumreg)) print(sumreg) ... options(ow) # reset } The routine userfn() is called multiple times, two of which I happen to know to

Dear all I tried to use regression to predicted mu data, but it has error like this: > IWJR.complete x y [1,] 33.17635 2.4705021 [2,] 81.61225 3.3815620 [3,] 65.47392 1.6518975 [4,] 57.97806 1.6110785 [5,] 76.05528 2.1601246 [6,] 41.36090 1.5498132 [7,] 68.77844 2.8078691 [8,] 55.57040 2.1183063 [9,] 41.29287 1.8015709 [10,] 65.43935 2.3483183 [11,] 22.44821

I'm running an LSODA to generate some graphs, but I need to stop at a certain point and use those values to generate another LSODA output. This is working fine, but when I try to run the second LSODA, I get the "Error in eval(expr, envir, enclos) : object 'N' not found". Any ideas what can be causing this? I have no object 'N' anywhere in the script. I made an

Hello. I have run the command imp<-mice(mydata, im=c("","pmm","logreg","logreg"),m=5)  for a variable with no missing data, a numeric one and two variables with binary data. I got the following message: There were 37 warnings (use warnings() to see them) > warnings() Warning messages: 1: In any(predictorMatrix[j, ]) ... : coercing argument of

Hello, I am a (relatively) experienced programmer, but new to R. I have a problem using R 1.9.1. I have fit some data using glm(), from within a function: formula = as.formula(paste(depvarname, "~", rhs), env=globalenv()) return (glm(formula, family=binomial(link=logit))) I have now come back to the formula and want to add some more variables to it. So I do:

Hi, I'm trying to fit a ordered logistic regression. The response variable (y) has three levels (0,1,2). The command I've used is: ordlog<-polr(y~x1+x2+x3+x4, data=finalbase, subset=heard, weight=wt, na.action=na.omit) (There are no NA's in y but there are NA's in X's) The error I'm getting is: Warning messages: 1: non-integer #successes in a binomial glm! in:

hello everybody I'm a newbie with ordered probit and with polr too. The problem is that I have a dependent variable I need to explain with an ordered probit that is > head(dfscale$sod.sit.ec.fam,100) > [1] 5 7 5 6 5 5 6 8 6 8 8 8 6 6 6 5 0 5 NA 6 > [21] 7 NA NA 0 0 2 5 3 6 6 7 6 NA 8 6 6 7 NA NA NA > [41] 4 5 NA 10 3 9 10 10 7 5 5 5 NA

Dear R experts: I am running some calculations using polr() in MASS library, and found some differences in results obtained on two different machines (IRIX 6.5, and Linux RH 7.1). It is not clear to me whether this is due to some error in my programming the calculation and how to resolve the differences, if possible. The polr() call is the following:

Hi, I am trying to write a function to compute many cross-tabulations with the -svytable- command. Here is a simplified example of the structure of my code (adapted from the -svytable- help file): data(api) func.example<-function(variable){ dclus1<-svydesign(id=~1, weights=~pw,data=apiclus1, fpc=~fpc) svytable(~ variable, dclus1) } When I call this function with: