similar to: Tobit model on unbalanced panel

Hi there, I need to run a Tobit Fixed Effects in a panel data with 4500 units for 8 years. It is a huge data set, my dependent variable is left truncated at zero, the distribution is skewed and my panel is balanced. Any suggestions on how to do that in R? I tried stuff like survreg, censReg, and tobit but none of them were satisfactory. Thanks, *Felipe Nunes* CAPES/Fulbright Fellow PhD

Hello! I'm thinking of applying a censored regression model to cross-sectional data, using either the tobit (package survival) or the censReg function (package censReg). The dependent variable is left and right-censored. My hopefully not too silly question is this: I understand that heteroskedasticity and nonnormal errors are even more serious problems in a censored regression than in an

Hi - First post, so excuse any errors in protocol: Wanted to ask if there's an easy way to use 'predict' with objects of class 'censReg', 'maxLik', 'maxim' or 'list'. Have a left-censored dataset, attempting to use a Tobit model and am working with the censReg package. I like how easy it is to move from glm models to predictions with

Hello all, I have a problem estimating Random Effects model using censReg function. small part of code: UpC <- censReg(Power ~ Windspeed, left = -Inf, right = 2000,data=PData_In,method="BHHH",nGHQ = 4) Error in maxNRCompute(fn = logLikAttr, fnOrig = fn, gradOrig = grad, hessOrig = hess, : NA in the initial gradient ...then I tried to set starting values myself and here is

Hello R-Users: I am want to use tobit regression for left censored panel/longitudinal data. Could you please provide me the name of "library" and/or "package" that will give me option of fitting tobit regression model for longitudinal data? Thank you. Sattar __________________________________________________ [[alternative HTML version deleted]]

I am trying to work out a bootstrapped Tobit regression model. I get the coefficients all right, but they all have standard error zero. And I am unable to figure out why. I know the coefficients are correct because that's what I get when do a Tobit (without bootstrapping). Here's my code: # Bootstrap 95% CI for Tobit regression coefficients? library(boot) library(AER) # for the Affairs

Hi, I'm trying to fit a tobit regression model to some data. When fitting the exact same data in Stata, I have no problems at all, however R won't converge. Its not a maxiters thing, since I've tried increasing this already. I need to be able to fit the model in R since there are users of the code that don't have a Stata license. The code is: require(AER) left = 3.218476 x =

I'm statistician I need help with tobit regression Is there assumption in tobit regression ? if any, what kind of that ? please help me !!

Hi all, Quick question - Which, if any, of the R packages contains procedures for running Tobit analysis? Regards, Matt --------------------------------- [[alternative HTML version deleted]]

Dear All: I need some guidance in calculating a goodness-of-fit statistic for a Tobit Regression model. To develop the Tobit regression, I used the tobit() method from the AER package, which is basically a simpler interface to the survreg() method. I've read about pseudo R2 and C-index and was wondering if there is a package that calculates this for me. Also, is there a reason to select

Dear All, we (Ott Toomet and I) would like to add functions for maximum likelihood (ML) estimations of generalized tobit models of type 2 and type 5 (*see below) in my R package for microeconomic analysis "micEcon". So far we have called these functions "tobit2( )" and "tobit5( )". Are these classifications well known? How are these functions called in other

Dear R-users, I would like to model data where the response variable consists of many minus ones and many different positive values that seem to follow an apparently separate distribution (ie. -1, -1, 0.5, -1, 3, 3.5, 1.2, -1, -1, 0.4, etc); no values of the response can be less than minus one or between minus and zero (exclusive). I am aware of tobit regression but unaware of exactly how to

Folks, Based on http://www.biostat.wustl.edu/archives/html/s-news/1999-06/msg00125.html I thought I should experiment with using survreg() to estimate tobit models. I start by simulating a data frame with 100 observations from a tobit model > x1 <- runif(100) > x2 <- runif(100)*3 > ystar <- 2 + 3*x1 - 4*x2 + rnorm(100)*2 > y <- ystar > censored <- ystar <= 0

Hi, what is the best way to estimate a tobit(truncated) regression model in R ? Is there already a packet available ? Gruss Ralph Leonhardt -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Hi all, I'm from Brazil. I fit a Tobit model to FLUID MILK CONSUMPTION (DEPENDENT VARIABLE) data using survreg (attached). I am confused about the output interpretation and I would like yours explanations. Thanks, Marcio Roberto Silva -------------- next part -------------- A non-text attachment was scrubbed... Name: Tobit model.pdf Type: application/pdf Size: 9018 bytes Desc: not

Hi all, Is there any code to run fixed effects Tobit models in the style of Honore (1992) in R? (The original Honore article is here: http://www.jstor.org/sici?sici=0012-9682%28199205%2960%3A3%3C533%3ATLALSE%3E2.0.CO%3B2-2) Cheers David [[alternative HTML version deleted]]

Does anyone have an R function for the estimation of Tobit regression models (for censored responses), as described, e.g., in Davidson, R. and MacKinnon, J.G., 1993, Section 15.7, Estimation and Inference in Econometrics, Oxford University Press? Thanks. FC. -- Francisco Cribari-Neto voice: +55-81-32718420 Departamento de Estatistica fax: +55-81-32747425 Universidade

Hi, R users, I'm running a Tobit model but convergence can not be reached within 30 iterations. Is there anyway I can change the max number of iterations? Thanks. Gary [[alternative HTML version deleted]]

Dear everyone: I am a new user of R. I have a dataset with a dependent variable (DV) censored at different values. The dataset looks like, conditions .....IDV1 IDV2 DV 1 2 4 89 1 6 6 75 1 4 5 0 ( DV<=70) ...... 2 3 5 15 2 5 5 0

Having read previous correspondance on this topic, am I right in using a gaussian distribution for a tobit model, one article suggests a normal distribution? Also, I want to censure at the upper bound, so, using the survival5 package I use: survreg(Surv(y,y<c,type="right")~x) for a censored regression. Could anybody who's had experience of this, confirm whether I'm in the