similar to: Likelihood optimization numerically

Dear friends, when i use glm() to fit my data, i use glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, *family = Gamma(link = inverse),* data =a,)) It shows: error in eval(expr, envir, enclos) : *gamma distribution don't allow negative value*. But i use result<-glm(formula = snail ~ vegtype + mhveg + humidity + elevation + soiltem, family = poisson, data =a) #this

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Dear all, I ran into problems with the function "optim" when I tried to do an mle estimation of a simple lognormal regression. Some warning message poped up saying NANs have been produced in the optimization process. But I could not figure out which part of my code has caused this. I wonder if anybody would help. The code is in the following and the data is in the attachment. da <-

> str(data) 'data.frame': 250 obs. of 3 variables: $ student: chr "A" "B" "C" "D" ... $ data : num 20.2 20.4 22.5 22.1 23.3 ... $ param : Factor w/ 4 levels "AGE","SCHOOL",..: 1 1 1 1 1 1 1 1 1 1 Hi , i would like to split the dataframe so that each level of param is a column At the end it should look like

I feel like a complete dolt, as I know this question has been asked by others on a fairly regular basis, but I'm going in circles trying to get the following to work: id.prob<-function (tt) { library(mvtnorm) #============================ Makeham<-function(tt) { a2=0.030386513 a3=0.006688287 b3=0.039047537 t<-tt-20 h.t<-a2+a3*exp(b3*t) S.t<-exp(-a2*t+a3/b3*(1-exp(b3*t)))

Hi: I am using R 1.7.0 on Windows. I am having trouble getting "outer" to work on one of my functions. Here is a simple example illustrating my problem: > b1 <- c(1.2,2.3) > b2 <- c(0.5,0.6) > x <- c(3e+01, 1e+02, 3e+02, 5e+02, 1e+03, 1e+04, 1e+05, 1e+06) > y <- c(2,4,2,5,2,3,1,1) > n <- c(5,8,3,6,2,3,1,1) > outer(b1,b2,FUN=bpllkd,x,y,n)

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

Hello, First time poster here so let me know if you need any more information. I am trying to run an ordered probit with maximum likelihood model in R with a very simple model (model <- econ3 ~ partyid). Everything looks ok until i try to run the optim() command and that's when I get " Error in rep(1, nrow(x)) : invalid 'times' argument". I had to adapt the code from a 4

Hello R Users, I am new to R. I have two data sets i) TOMS aerosol optical depth(AOD) and ii) TOMS ozone(O3). > > AOD data is on 1x1 grid and O3 data is on 5x5 grid. > > First I want to read AOD and O3 as it is and then I want to regrid AOD on > 5x5 grid as O3. > > Reading is first problem. > > FIRST PROBLEM READING AOD: > > AOD data is in following format: >

The partial R-square (or coefficient of partial determination, or squared partial correlation coefficients) measures the marginal contribution of one explanatory variable when all others are already included in multiple linear regression model. The following link has very clear explanations on partial and semi-partial correlation: http://www.psy.jhu.edu/~ashelton/courses/stats315/week2.pdf In

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If I'm not mistaken, partial R-squared is the R^2 of the quantities plotted in a partial residual plot, so you can base the computation on that. Prof. Fox's `car' package on CRAN has a function for creating those plots, but you need to figure out the way to extract the quantities being plotted. [In any case, the basic tools for doing such computations are all in R, and it

I'm looking at what would be involved in converting from MeetMe to ConfBridge and there seems to be a lot of missing administrative things, but I hope I'm just missing it. We all know about the missing realtime linkage. That's a major nuisance, but can be worked around. More serious is that the CLI command to display users in a ConfBridge don't show the caller ID information, so

I'm using a very long irregular time-series of air temperature and relative humidity of this kind (this is an extract only) its.format("% Y%d%m %X) > base T H 20020601 12.00.00 27.1 47 20020601 15.00.00 29.1 39 20020601 18.00.00 27.4 39 20020601 21.00.00 24.0 40 20020602 0.00.00 22.0 73 20020602 3.00.00 19.2 49 20020602 6.00.00 19.5 74 20020602

hi - in version 2.1 the command >-2^2 gives -4 as the answer. (-2)^2 is evaluated correctly. Cheers, George Casella -- George Casella Phone: (352) 392-1941 Ext. 204 Distinguished Professor and Chair Cell: (352) 682-7210 Department of Statistics Fax: (352) 392-5175 University of Florida Email: casella at stat.ufl.edu P.O. Box 118545 Gainesville, FL

hi - in version 2.1 the command >-2^2 gives -4 as the answer. (-2)^2 is evaluated correctly. Cheers, George Casella -- George Casella Phone: (352) 392-1941 Ext. 204 Distinguished Professor and Chair Cell: (352) 682-7210 Department of Statistics Fax: (352) 392-5175 University of Florida Email: casella at stat.ufl.edu P.O. Box 118545 Gainesville, FL

*Hello, I'm new to R and trying to do Split Split Plot Design analysis with aov function in R. Sharing any worked example and suggestion will be highly appreciated. Thanks Regards! * -- * Muhammad Yaseen * [[alternative HTML version deleted]]

Hi folks, I am running a very simple regression using mylm <- lm(mass ~ tarsus, na.action=na.exclude) I would like the use the residuals from this analysis for more regression but I'm running into a snag when I try cbind(mylm$residuals, mydata) # where my data is the original data set The error tells me that it cannot use cbind because the length of mylm$residuals is

Dear all, quite a naive question: I have a data frame and I computed "the kernel density estimate" with density on each column. Now I'd like to export in a txt file the density function output for each column, but, when if I use write.table, I get a message "Error in as.data.frame.default(x[[i]], optional = TRUE) : can't coerce class "density" into a

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2