similar to: "New" problem with polr (or optim, or ...)

Hi, I'm getting an error message using polr(): Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) : initial value in 'vmmin' is not finite The outcome variable is ordinal and factored, and the independant variable is continuous. I've checked the source code for both polr() and optim() and can't find any variable called

Hello again I am trying to fit an ordinal logistic model using the polr function from MASS. When I run model.loan.ordinal <- polr(loancat~age + sex + racgp + yrseduc + needlchg + gallery + sniffball + smokeball + sniffher + smokeher + nicocaine + inject + poly(year.of.int,3) + druginj + inj.years) I get an error Error in optim(start, fmin, gmin, method = "BFGS", hessian =

Hi all. I'm just starting to explore ordinal multinomial regression. My dataset is 300,000 rows, with an outcome (ordinal factor from 1 to 9) and five independent variables (all continuous). My first stab at it was this: pomod <- polr(Npf ~ o_stddev + o_skewness + o_kurtosis + o_acl_1e + dispersal, rlc, Hess=TRUE) And that worked; I got a good model fit. However, a variety of other

Hello, I have used R in the past to conduct multiple comparisons on standard linear models, but am a bit confused as to how to go about doing it with a mixed effects model. I am conducting a bioindication study using carabid beetles in which I have four treatment types (forest harvest types with varying levels of canopy structure retention), and am using canopy closure percent as a covariate in

Hello R-users, I am using polr function in library(MASS). The code I use is the following: polr(as.ordered(q23p)~.,data=as.data.frame(datapr2)) where datapr2 is a matrix of 63 columns (together with the dependent variable) and 1665 rows. But I am receiving the warning message Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) I would be very greatfull if anyone

Hi, I have a problem with initial value for optim in polr that R report. After a call to polr, it complains that: Error in optim(start, fmin, gmin, method="BFGS", hessian= Hess, ...) : initial value in 'vmin' is not finite. Would you please suggest a way round to this problem? Thank you so much in advance. Rgds, - adschai

Apologies for this - I'm sure I'm missing something somewhere... I've got a time series with several of missing values in it that I want to torture with R. But ts doesn't like the NA's, and I can't find any documentation telling me what to do about it. Help! Bob -- Bob O'Hara Metapopulation Research Group Division of Population Biology Department of Ecology and

Dear Sir, I get an error message when I use polr() in MASS package. My data is "ord.dat". I made "y" a factor. y y1 y2 x lx 1 0 0 0 3.2e-02 -1.49485 2 0 0 0 3.2e-02 -1.49485 3 0 0 0 1.0e-01 -1.00000 4 0 0 0 1.0e-01 -1.00000 5 0 0 0 3.2e-01 -0.49485 6 0 0 0 3.2e-01 -0.49485 7 1 1 0 1.0e+00 0.00000 8 0 0 0 1.0e+00 0.00000 9 1 1 0

Dear all, I get an error message when I use polr() in MASS. These are my data: skugg grupp frekv 4 1 gr3 0 5 2 gr3 3 6 3 gr3 6 10 1 gr5 1 11 2 gr5 12 12 3 gr5 1 > > summary(polr(skugg ~ grupp, weights=frekv, data= skugg.cpy1.dat)) Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :

In polr.R the (several) functions gmin and fmin contain the code > theta <- beta[pc + 1L:q] > gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100) That's bad. There's no reason to suppose beta[pc+1L] is larger than -100 or that the cumulative sum is smaller than 100. For practical datasets those assumptions are frequently violated, causing the

Dear R-user I used lme to fit a linear mixed model inlcuding weights=varPower(). Additionally I wanted to use glht to calculate Tukey-Kramer multiple comparision. error: > glht(modelF, linfct=mcp(Species="Tukey")) Error in glht.matrix(model = list(modelStruct = list(reStruct = list(SubPlot = -0.305856275920955, : ?ncol(linfct)? is not equal to ?length(coef(model))? >

Dear members of the list, I'm fitting ordinal regressions using polr, and in some models I get the error copied below. Dependent variable is an ordered factor of bird abundance categories, and predictors are continuous habitat variables. > ro6 <- polr(formula = abun ~ InOmbrot + Oliva.OC + ToCultAr + DivCulArb + AltitMax + COORXY) > summary(ro6) Re-fitting to get Hessian

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:

Dear Colleagues, I hope to know how ordinal logistic regression with a mixed model is made in R. We (My colleague and I) are studying the behavior of a beetle. The attraction of beetles to a stimulus are recorded: the response is Slow, Mid, or Fast. They are based on the time after the presentation of the stimulus to the beetles. Because we do not observe the behavior continuously but do

Dear All, I have a dataframe made up of individual beetles consisting of individual number, family number, mother's family number, father's family number, and sex of the beetle. I would like to pair up the individuals for breeding. I would, however, like to avoid breeding beetles of the same sex (obviously), the same family, and with the same mother's family or father's family,

Dear R-users, is there a chance to do an nested ANCOVA in R? I've read the archive mails but it doesn't work. We have the following situation: We are interested in differences in carabid biomass at different aged woodlands. Thus, we have a nested design with 2 fixed groups (0=recent, 1=ancient) and 10 woodlands (each with 8 replications/traps) per fixed group. Woodland is therfore

Hi (1)In polr(), is there any way to calculate a pseudo analogue to the R^2. Just for use as a purely descriptive statistic of the goodness of fit? (2) And: what are the assumptions which must be fulfilled, so that the results of polr() (t-values, etc.) are valid? How can I test these prerequisites most easily: I have a three-level (ordered factor) response and four metric variables. many

>> Can I change my vote to http://samugliestdog.com/Sam162edited.jpg yikes! how''d that get past my firewall? +1 On 6/30/06, mongrel-users-request at rubyforge.org <mongrel-users-request at rubyforge.org> wrote: > Send Mongrel-users mailing list submissions to > mongrel-users at rubyforge.org > > To subscribe or unsubscribe via the World Wide Web, visit

I'm running polr() and getting warning messages from glm.fit(). It seems reasonable to use glm.control() to turn on the trace and follow what glm.fit() does when called by polr(); or is it? glm.control(maxit=10, trace=TRUE) polr(act~., data=mm) The glm.control() sets the trace TRUE, but there's no change in the output from polr(). Many thanks in advance for any help/pointers.

Dear community, I am currently trying to fit an ordinal logistic regression model with the polr function. I often get the same error message : "attempt to find suitable starting values failed", for example with : require(MASS) data(iris) polr(Species~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width,iris) (I know the response variable Species should be nominal but I do as levels