similar to: Censored or truncated Regression Models/Tobit

I wonder if there is a package that will estimate a Zero Inflated Poisson Model (ZIP), and also if there is a package that will estimate what is called the Tobit model: that is a combination of censored and observed values in the same sample. Georgina Bermann Biostatistics AstraZeneca R&D M?lndal -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

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

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

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

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]]

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

Appreciate any suggestions regarding how to fit an unbalanced panel data to a Tobit model using R functions. I am trying to analyze how real estate capital expenditures (CapEx) are affected by market conditions using a panel Tobit model. The CapEx is either positive or 0, so it is censored. The data are unbalanced panel, including the CapEx of about 5000 properties over about 40 quarters, with the

Hello, I have interval censored data, censored between (0, 100). I used the tobit function in the AER package which in turn backs on survreg. Actually I'm struggling with the distribution. Data is asymmetrically distributed, so first choice would be a Weibull distribution. Unfortunately the Weibull doesn't allow for zero values in time data, as it requires x > 0. So I tried the

Dear R-user: I have a left censored longitudinally measured data set with 4 variables such as sub (which is id), x (only covariate), y (repeatedly measured response) and w (weights) (note, ?-5? indicates the left censored value in the attached data set). I am using following R codes (?survival? library and ?survreg? package) for fitting a random effect tobit model for the left censored

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

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]]

Hi, Problem: I have the ususal linear regression model y=Xb but I cant observe y (expenditure for a particular good) for some y <c where c is fixed for all observations. But I can observe the corresponding covariates x (incom). I used the survivla5 library (survreg(Surv(y,y<c,type="left")~x) for a censored regression model (thanks again for this tip). Is there a way to estimate

Dear R-helpers, excuse me if this is not exclusively an R-related question. I have data from a nested design, both temporally and spatially, and the reponse variable of interest is left-censored. That is, only values > "some treshold" are available, otherwise "LOW" is reported. Are there ways of building a linear model with both fixed and random effects, when the

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

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, 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 =

Dear R-user: I am using survreg(Surv()) for fitting a Tobit model of left-censored longitudinal data. For logarithmic transformation of y data, I am trying use survreg.distributions in the following way: tfit=survreg(Surv(y, y>=-5, type="left")~x + cluster(id), dist="gaussian", data=y.data, scale=0, weights=w) my.gaussian<-survreg.distributions$gaussian

I need to give a quick description of Tobit Regression (TR), including how it differs from ordinary least squares (OLS). I am an ecologist who knows just enough about remote sensing and statistics to be dangerous in both. Now I have found myself doing a remote sensing project where I have used TR: survreg(Surv()). As far as I can tell, no form of Censored Regression has been used in analyzing

Hello, I have been googling for 2 days and I cannot find the answer in previous posts. I have a set of d-dimensional data elements (d=11 .. 14), each data point can be censored at different values both Lower-limit and upper limit. N = 2000 sets of vectors of D=11 data points per vector. Each of the N*D points can have different upper and lower limits. I "simply" want to fit a

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