similar to: Probit regression with limited parameter space

Hi R users, I am trying to restrct the range of two of the parameters in a maximization problem. Both parameters should be between -1 and 1. As far as I know, if I choose the estimation method ="L-BFGS-B" under Optim, I can restrict the parameter space. However, the "L-BFGS-B" always require finite values of the loglik function and cannot get around of the problem if an

I was just curious if anyone knew of an alternative model to logistic regression where the probabilities seems pretty linear to the predictor rather than having that S shape that probit and logit assume. Maybe there is there some kind of other GLM that could accomplish that. Any textbook references or suggestions are appreciated. I have most of the texts but if someone knows of a text that talks

Hi R users, I am trying to call openbugs from R. And I got the following error message: ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ model is syntactically correct expected the collection operator c error pos 8 (error on line 1) variable ww is not defined in model or in data set [1] "C:\\DOCUME~1\\maomao\\LOCALS~1\\Temp\\RtmpqJk9R3/inits1.txt"

Dear R Help, I have two nested negative log-likelihood functions that I am optimizing with the spg function [BB package]. I would like to perform model selection on these two objective functions using AIC (and possibly anova() too). However, the spg() function returns a list and I need a fitted model object for AIC(), ICtab() [bbmle package], or anova(). How can I perform AIC-based model

Hi R-helpers, Is it possible that I have the estimates from each step/iteration shown on the computer screen in order to monitor the process while I am using Optim or MaxLik? Thanks for your help. Maomao [[alternative HTML version deleted]]

I am trying to write a wrapper for the last example in help(cv.glm) that deals with leave-one-out-cross-validation (LOOCV) for a logistic model. This wrapper will be used as part of a bigger program. Here is my wrapper funtion : logistic.LOOCV.err <- function( formu=NULL, data=NULL ){ cost.fn <- function(cl, pred) mean( abs(cl-pred) > 0.5 ) glmfit <- glm(

Hi R users, I need to draw a map of select European countries with country names shown on the map. Does anyone know how to do this in R? Also, is it possible to draw a historical map of European countries using R? Thanks a lot for your help. Maomao [[alternative HTML version deleted]]

Dear all, I've been having problems running update() to re-fit a cpglm model inside a function (as in the code below). The solution is probably simple, but I'm stuck. If anyone could help, I'd greatly appreciate it. Regards, Rubem ## R code library(cplm) ## Data simulation period<-factor(1:4)                        herd<-factor(1:50)  

#I would like to use the below data to make a scatter plot matrix with #code similar to that below the data #conceptually this is the right approach I think #thanks in advance melt.gg <- structure(list(stream = c("Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower",

Dear Help, Suppose I have a character vector. x <- c("Bob", "loves", "Sally") I want to combine it into a single string: "Bob loves Sally" . paste(x) yields: paste(x) [1] "Bob" "loves" "Sally" The following function combines the character vector into a string in the way that I want, but it seems somewhat inelegant.

If I have a dataframe which is organized like this: name color likes? 1 sally red 0 2 sally blue 1 3 sally green 1 4 jake red 0 5 jake blue 1 6 jake green 1 7 tom red 1 8 tom blue 0 9 tom green 0 And I want to create a matrix in the form: red blue green sally 0 1 1 jake 0 1 1 tom 1 0 0 Are there any built-in

The mle2 function (bbmle library) gives an example something like the following in its help page. How do I access the coefficients, standard errors, etc in the summary of "a"? > x <- 0:10 > y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8) > LL <- function(ymax=15, xhalf=6) + -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE)) > a <- mle2(LL,

Dear All, I am trying to reshape the data with some conditions. A small part of the data looks like below. Like this there will be more data with repeating ID. Count id name type 117 335 sally A 19 335 sally A 167 335 sally B 18 340 susan A 56 340 susan A 22 340 susan B 53 340 susan B 135 351 lee A 114 351 lee A 84 351 lee A 80 351 lee A 19 351 lee A 8 351 lee A 21 351 lee A 88 351 lee B 111 351

Hi sri, As your problem involves a few logical steps, I found it easier to approach it in a stepwise way. Perhaps there are more elegant ways to accomplish this. svdat<-read.table(text="Count id name type 117 335 sally A 19 335 sally A 167 335 sally B 18 340 susan A 56 340 susan A 22 340 susan B 53 340 susan B 135 351 lee A 114 351 lee A 84 351 lee A 80 351 lee A 19 351 lee A 8 351 lee A

Hi all, I have downloaded the latest version of wine in order to run iTunes but when I tried to execute the program here is what I get : cd /home/sally/Documents $ wine iTunes64Setup.exe Trying to load PE image for unsupported architecture (AMD-64) err:process:create_process starting 64-bit process L"Z:\\home\\sally\\Documents\\iTunes64Setup.exe" not supported on this platform wine:

Dear R users, I have been trying to obtain the MLE of the following model state 0: y_t = 2 + 0.5 * y_{t-1} + e_t state 1: y_t = 0.5 + 0.9 * y_{t-1} + e_t where e_t ~ iidN(0,1) transition probability between states is 0.2 I've generated some fake data and tried to estimate the parameters using the constrOptim() function but I can't get sensible answers using it. I've tried using

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Dear Sir/ Madam, I'm having trouble de-bugging the following - which works perfectly well with optim or optimx - but not with mle2. I'd be really grateful if someone could show me what is wrong. Many thanks in advance. JSC: gompertz<- function (x,t=data) { a3<-x[1] b3<-x[2] shift<-data[1] h.t<-a3*exp(b3*(t-shift))

Hi everybody, I am using the L-BFGS-B method of the mle2() function to estimate the values of 6 parameters. mle2 uses the methods implemented in optim. As I got it from the descriptions available online, one can use the parscale parameter to tell R somehow what the values of the estimated parameters should be . . . Could somebody please help me understand what one has to do actually with the

Hi Jim, Thanks for your time. But somehow this code did not help me to achieve my expected output. Problems: 1) x, y are coming as logical rather than values as I mentioned in my post 2) The values that I get for Max A and Max B not correct 3) It looks like a pretty big data, but I just need to concatenate the values with a comma, the final output will be a character