similar to: Count function calls

Dear all I am trying to fit Variable Coefficients Models on Unbalanced Panel Data. I managed to fit such models on balanced panel data (the example from the "plm" vignette), but I failed to do so on my real, unbalanced panel data. I can reproduce the error on a modified example from the vignette: > require(plm) > data("Hedonic") > Hed <- pvcm(mv ~ crim + zn + indus

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

Dear r-helpers, I am working with plm package. I am trying to fit a fixed effects (or a 'within') model of the form y_it = a_i + b_i*t + e_it, i.e. a model with an individual-specific intercept and an individual- specific slope. Does plm support this directly? Thanks in advance! Otto Kassi

Hello everybody, I have a problem with the the function PVCM in the plm package: I have an unbalanced panel with over 200 companies and 1 to 14 years for each company. I already excluded all NAs: > dataset<-na.omit(dataset) Now I'm trying to fit a variable coefficients model: > model_vc <- pvcm(v1 ~ lag(v2,1), model="within", data=dataset) This results in the

Hi all, I am quite new in the world of parallelization and I wonder if there is a way to increase the speed of creation of a parallel socket cluster. The time spend to include threads increase exponentially with the number of thread considered and I use of computer with two 8 cores CPU and thus showing a total of 32 threads in windows 7. Currently, I use the default parameters (type =

Dear R community, I do know, that an R function is constructing a copy of any object passed as argument into a function. I program on a larger S4 project for a package, and I arrived at a point where I have to think a little harder on implementation style (especially to spare users complex object handling). I have a function foo(), taking as input arguments two S4 objects of different class

Is there anyway with some experience in using armadillo in R C++ extensions? My problem is the following: I programmed a function in a header looking like #include <armadillo> inline arma::vec foo(input) { ... do something return an arma::vec object } compiling this via R CMD INSTALL packagename (PKG_CXXFLAGS = -I/folder/of/armadillo and armadillo_bits in my package) I get the

When using the PLM package (version 1.2-8), I encounter the probem that calling the FGLS estimator evokes strange behavior, when choosing the "random" effects model. After calling the PGGLS function to estimate FGLS, PLM gives me a warning, stating that the "random" model has been replaced with the "pooling" model. I would, however, really like to estimate the random

Dear Sir/ Madam, I am writing about the panel data for my bachelor degree. I would really appreciate if You could help dealing with R functions. I am trying to estimate the panel data lm model with plm function. When i include 3dummy variables into the regression it dont appear in the sumarry of the model, but when i estimate a simple lm model it appears. Why is it so? What should i do to

Hi everyone, I am using package knitr, FIRST TIME. I don't have access to RStudio. Read through Yihui's page, didn't find it helpful. Stuck on terms Rnw, GFM (GitHub Flavored Markdown). Never used Sweave, so the reference is not helping. Is there a simple step-by-step example WITHOUT RStudio? My question: What is the procedure? The documentation explains the functions, but does

I'd like to announce three new packages on CRAN: pmg, gWidgets, and gWidgetsRGtk2. --John Verzani 1 PMG *=*=*= The pmg package for R provides a relatively simple graphical user interface for R in a manner similar to the more mature RCmdr package. Basically this means a menu-driven interface to dialogs that collect arguments for R functions. This GUI was written with an eye towards

I'd like to announce three new packages on CRAN: pmg, gWidgets, and gWidgetsRGtk2. --John Verzani 1 PMG *=*=*= The pmg package for R provides a relatively simple graphical user interface for R in a manner similar to the more mature RCmdr package. Basically this means a menu-driven interface to dialogs that collect arguments for R functions. This GUI was written with an eye towards

Hello. Not an easy question at all, and it has little to do with software, alas! Veeeeeery loosely speaking: if the homogeneity hypothesis is rejected, then, depending on data availability, you may still be able to treat the data like a panel by: a) ignoring the results of the poolability test b) allowing the coefficients to vary. Of course, a) requires some courage while b) requires more

Hi,R 2.15.2 plm() function on Windows 7 when i perform a plm regression, i can't manage to obtain the intercept, but I need it.it gives me just the beta coefficient. my formula: fixed <- plm(deltaS ~ L1.deltaS + L2.deltaS, data=Mody_R, index=c("country_id", "date"), model="within") my output: Coefficients : Estimate Std. Error t-value Pr(>|t|)

Hi Graham, Your guess is right. The event loop stuff is handled differently on Windows than on Unix-like OSes. There is a hook, called tcl_do that is hard-coded into the R Windows GUI. It is called whenever the console is idle. RGtk2 is able to hook into that to process GTK+ events. The problem is that the two packages replace each other's handler. So in this case tcltk is blocking GTK+ from

Hi all, I a semi-beginner with R and I am working with the plm package to examine a longitudinal dataset. Each individual in this dataset has a longitudinal weight for the probability that he or she remains in the sample. Unfortunately, I have not found an argument to use weights in the plm function? I tried ?weights=? like in standard lm or in nlme or lm4 but it does not work. I asked the

dear readers---I struggled with how to do nice fixed-effects regressions in large economic samples for a while. Eventually, I realized that nlme is not really what I needed (too complex), and all I really wanted is the plm package. so, I thought I would share a quick example. ################ sample code to show fixed-effects models? in R # create a sample panel data set with firms and years

Hi everybody, Got some doubts here. I'm kinda desperate for help, so please ask me if anything isn't clear. I have a database with this structure (panel data structure): > head(dados_2) Tempo Safra Data Resposta Perc_Resg_Acum Alta_Temporada Flexi Promo 1 1 1 200701 0.04223216 0 1 0 0 2 1 2 200702 0.02801536 0

Hello, I am trying to run a fixed effects panel regression on data containing 5 columns and 1,494 rows. I read the data in as follows: >drugsXX<-read.csv(file="C:\\Folder\\vX.X\\Drugs\\drugsXX_panel.csv", head=TRUE, sep=",") Verified it read in correctly and had a good data.frame: >dim(drugsXX) [1] 1494 5 >drugs XX produce expected data with correct column

Dear R Experts--- Sorry for all the questions yesterday and today. I am trying to use Yves Croissant's pgmm function in the plm package with Blundell-Bond moments. I have read the Blundell-Bond paper, and want to run the simplest model first, d[i,t] = a*d[i,t-1] + fixed[i] + u[i,t] . no third conditioning variables yet. the full set of moment conditions recommended for system-GMM,