similar to: PGLM Package: Starting Values for Within-Model

I'm using the package pglm and I'have estimated a "random probit model". I need to save in a vector the fitted values and the residuals of the model but I can not do it. I tried with the command fitted.values using the following procedure without results: library(pglm) m1_S<-pglm(Feed ~ Cons_PC_1 + imp_gen_1 + LGDP_PC_1 + lnEI_1 +

Dear Sir, When requesting the summary of pglm analyses in R, I encounter repeatedly the following warning message: "Warning message: In pf(Fstat, object$k - 1, object$n - object$k, ncp = 0, lower.tail = FALSE, : full precision was not achieved in 'pnbeta'" This message appears both with the pglm estimate of Lambda and with Lambda set to 0. Could you tell me what

Hi, I'm trying to do a regression like this: wage.r = lm( log(WAGE) ~ log(EXPER) where EXPER is an integer that goes from 0 to about 50. EXPER contains some zeros, so you can't take its log, and the above regression therefore fails. I would like to make R accept log(0) as 0, is that possible? Or do I have first have to turn the 0's into 1's to be able to do the above

Dear all, How do I obtain the number of countries that my panel models estimated by pglm() and relogit() (the latter one is in the Zelig library) use? I couldn't find any information on that in the help files. Thank you very much in advance. Best wishes

I am a student who is doing empirical work for his thesis and trying to switch to R. I am familiar with Stata, and at the moment I am trying to replicate some of my previous work. I have a large unbalanced panel data set, observations for different countries between 1970 and 2007. My dependent variable is an overdispersed count. So far I have used fixed-effects negative binomial regression,

Hi, I try to execute the seven lines of code below to plot a graph. But I am failing as the messages below show. Where am I going wrong? install.packages("rgl") library(rgl) y_hat = X%*%B_hat open3d(windowRect = c(100,100,900,900),family = "serif") color = rainbow(length(y_hat))[rank(y_hat)] plot3d(educ,exper,wage,col = color,type = "s",size = 0.5,xlim =

Dear R-Help, My problem/bug came to light,when fitting a linear model using stepwise selection. I'd started with the straightfoward command step(lm(y~., dataset)) This worked fine, but because this starts with all the possible explanatory variables, it results in a model with too many explanatory variables. Hence I wanted to start with just a constant and do forward selection, to get a

It would be really nice if nlm took a set of "..." optional arguments that were passed through to the objective function. This level of hacking is probably slightly beyond me: is there a reason it would be technically difficult/inefficient? (I have a vague memory that it used to work this way either in S-PLUS or in some previous version of R, but I could easily be wrong.) Here's

Hola a todos, Necesito estimar dos parametros utilizando la función nlm; fit<-nlm(hood2par,c(x01[i],x02[j]),iterlim=300, catch=x[,c(3,4,5)],sp=.5) donde hood2par es una logística modificada. Pero en mi caso, la convergencia de nlm depende de los valores iniciales de dichos parámetros. Para buscar dichos valores iniciales de manera automática, genero dos vectores de valores iniciales

Dear Sir/ Madam,   I have some enquiry in R about maxLik package where, in this package we have the usage  maxLik(logLik, grad, hess, start, method, iterlim, print.level)   when I used this with print.level equals to 3 I could have estimates of parameters at each iteration but I do not know how can I call the information in the level. Is there any way can help me to call the information within

GENERAL REFERENCE ON NONLINEAR OPTIMIZATION? What are your favorite references on nonlinear optimization? I like Bates and Watts (1988) Nonlinear Regression Analysis and Its Applications (Wiley), especially for its key insights regarding parameter effects vs. intrinsic curvature. Before I spent time and money on several of the refences cited on the help pages for "optim",

Dear expeRts, first of all I'd like to thank you for the quick help on my last which() problem. Here is another one I could not tackle: I have data on an absorption measurement which I want to fit with an voigt profile: fn.1 <- function(p){ for (i1 in ilong){ ff <- f[i1] ex[i1] <- exp(S*n*L*voigt(u,v,ff,p[1],p[2],p[3])[[1]]) } sum((t-ex)^2) } out <-

Dear R users, I am new to R. I would like to find *maximum likelihood estimators for psi and alpha* based on the following *log likelihood function*, c is consumption data comprising 148 entries: fn<-function(c,psi,alpha) { s1<-sum(for(i in 1:n){(c[i]-(psi^(-1/alpha)*(lag(c[i],-1))))^2* (lag(c[i],-1)^((-2)*(alpha+1)) )}); s2<- sum(for(m in 1:n){log(lag(c[m],-1)^(((2)*alpha)+2))});

Hi, my first email, I hope I don't violate any rules. I want to run a panel (cross-section-time-series) regression with fixed effects. I have count data (patent citations) so a Poisson distribution applies. But I also want to control for over-dispersion and and excess zeros. I think I read all manuals of potentially helpful packages but I could not find a way to realise this. The closest I got

Hello R Community, I've been run the following codes. However, I've been getting an unusual segfault that I'm unable to trace its origin. Please give me a light to decipher the "caught segfault" Thanks for you attention. Bernardo. > options(STERM='iESS', editor='emacsclient') > rm(list = ls()) > > source("fgenIGLD.R") #RNG

Hello all samba users and programmers, Since I changed my system and reinstalled samba funny things happen in my net. I used to work with a Gentoo system and now I've got installed a Knoppix 3.2 Debian, but by now I don't think it's interesting for the problem I've got. What I did was: - install samba 3.0.0-final - copy the old smb.conf file to the path in the new system

Hi, First of all, thanks for your help. I have made some test with this results debian testing with xen 4.4 can run if we add mmcfg=0 as boot options to kernel boot parameters !!! Remember that with xen kernel <=4.0 works perfect without to add mmcfg=0 I have tried to install citrix xenserver 5.6 and works perfect (remember that this is xen 3 branch) Also we have tried to install xenserver

Hi, I am new to R. My problem is with the ordered logistic model. Here is my question: Generate an order discrete variable using the variable wrwage1 = wages in first full calendar quarter after benefit application in the following way: * wage*1*Ordered *= 1 *if*0 *· wrwage*1 *< *1000 2 *if*1000 *· wrwage*1 *< *2000 3 *if*2000 *· wrwage*1 *< *3000 4 *if*3000 *· wrwage*1 *<

Dear R-help, I am having trouble with the predict function in lasso2. For example: > data(Iowa) > l1c.I <- l1ce(Yield ~ ., Iowa, bound = 10, absolute.t=TRUE) > predict (l1c.I) # this works is fine > predict (l1c.I,Iowa) Error in eval(exper,envir, enclos) : couldn't find function "Yield" And I have similar trouble whenever I use the newdata argument in

I am trying to view the source code of the function nlm in the stats package of R 2.4.1. I downloaded the source from CRAN and opened nlm.R, and it calls a .Internal function: .Internal(nlm(function(x) f(x, ...), p, hessian, typsize, fscale, msg, ndigit, gradtol, stepmax, steptol, iterlim)) This is the same thing I saw when entering the function name at the R command