similar to: plm ? tests of poolability ? error: insufficient number

Hi everyone! I?m running the pooltest in plm package, like this pooltest(cstfin12~lmaccdiscrz+lcobjur+lliq+lcollateral+ldimensao, data = dados3, model = "within") But I got the following error: Error in FUN(X[[1L]], ...) : insufficient number of observations My data is an unbalanced panel with 20907 observations (6971 individuals and years 2001 to 2007). This is not enough?

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

Good day R-listers, My question is more a statistical question than an R related question, so please bear with me i'm currently applying the chow test of poolability in fact i'm working with panel N=17 T=5 , and my model looks like this : Yit= a0+B1X1+B2X2+B3X3+B4X4+eit My question is the following when i'm Testing for the equality of the coefficients of the unpooled data (the

Dear All, I'm trying to use waldtest to test poolability (parameter stability) between two logistic regressions. Because I need to use robust standard errors (using sandwich), I cannot use anova. anova has no problems running the test, but waldtest does, indipendently of specifying vcov or not. waldtest does not appear to see that my models are nested. H0 in my case is the the vector of

Dear list, dear Cecilia and Daniel, sorry for coming in ten days late, I've been very busy lately so I came across this email only today. This is just to make some points clearer re: fixed effects and r2 in package 'plm', to both you and the list. In particular, to make you aware of some additional features. Please see my comments below, with '##'. Best, Giovanni

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

In the rockchalk package, I want to provide functions for regression objects that are "well behaved." If an object responds to the methods that lm or glm objects can handle, like coef(), nobs(), and summary(), I want to be able to handle the same thing. It is more difficult than expected to ask a given fitted model object "do you respond to these functions: coef(), nobs(),

> On Mar 31, 2016, at 1:00 PM, Paul Johnson <pauljohn32 at gmail.com> wrote: > > In the rockchalk package, I want to provide functions for regression > objects that are "well behaved." If an object responds to the methods > that lm or glm objects can handle, like coef(), nobs(), and summary(), > I want to be able to handle the same thing. > > It is more

Small correction to my previous email: the error can also be replicated by installing the package and then sourcing the tests. This is slightly faster than running R CMD check. It is also how we ran the tests with gdb. This will run the tests in a Docker container and raise the same error. (To run outside of a Docker container, simply leave out the first line). docker run --rm -ti pooltest

Good day R-users, So if the question may seem easy to many of you but this present a serious issue for me . I'm currently running a panel data analysis i've used the plm package to perform the Tests of poolability as results intercepts and coefficients are assumed different. so my question is should give up the panel analysis in my case or is there any alternative methodology or

Hi, Try this: final3New<-read.table(file="real_data_cecilia.txt",sep="\t") dim(final3New) #[1] 5369??? 5 #Inside the split within split, dummy==1 for the first row.? For lists that have many rows, I selected the row with dummy==0 (from the rest) using the #condition that the absolute difference between the dimensions of those rows and the first row dimension was minimum

Hello, Could anybody offer any advice about implementing a Kohonen self organizing map for categorical data? Specifically I am wondering if there are any pre-existent packages that can deal with categorical data and/or how one would compare the input vector of categoricals with the self organizing map nodes. Thanks in advance. George Chen ----- Original Message ----- From: r-help-request at

Hi, Try this: which(duplicated(res10Percent)) # [1] 117 125 157 189 213 235 267 275 278 293 301 327 331 335 339 367 369 371 379 #[20] 413 415 417 441 459 461 477 479 505 res10PercentSub1<-subset(res10Percent[which(duplicated(res10Percent)),],dummy==1)? #most of the duplicated are dummy==1 res10PercentSub0<-subset(res10Percent[which(duplicated(res10Percent)),],dummy==0)

Thank you all!!! The problem was the decimal symbol! My data was saved in a txt file, so I?ve introduced the dec="," in ?read.table? and it worked. What I?ve done was coeficientes<-read.table("coeficientes.txt",sep="\t",header=T,dec=",") Then, subset worked fine coeficientesWanted<-subset(coeficientes,b1>0) Thanks again, Cec?lia Carmo

--- the forwarded message follows --- -------------- next part -------------- An embedded message was scrubbed... From: "Cecilia Carmo" <cecilia.carmo at ua.pt> Subject: Re: [R] subset dataframe/list Date: Mon, 01 Jun 2009 21:33:15 +0100 Size: 3657 URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20090601/921f7638/attachment-0002.mht>

Hi all, I am modelling a time series with missing data. *Q1)* However, I am not sure if I should use the next *graphics* to understand my data: *a)* ACF & PACF (original series) *b)* ACF & PACF (residuals) * * *Q2)* I am using *tsdiag*, so I obtain a graphic with 3 plots: stand. residuals vs time; acf for residuals; Ljung-Box for residuals (it is wrong for residuals). I know that using

Hi there, I have a question regarding a data set that looks like the following: 8 repeated measurements for 3 dosage levels. However, the measurements for each dosage levels are taken on a different group of subjects. example: subject time dosage measure 11         1          1          154 11         2          1          150 :          :           :             : 11        

Gentlemen, Forgive me if I am posting at the wrong place! I was going to test the "new" chan_ooh323 driver so I did install: debian: Linux sip2 2.6.26-2-686 #1 SMP dahdi-linux-complete-2.2.0.2+2.2.0 Asterisk SVN-trunk-r231692 Did enable chan_ooh323, everything compiled without any problems. Hardware setup: Phone (975) - Avaya CM - H.323 - Asterisk - X-Lite (0317998975) X-Lite can

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Hello all, I´m trying to study a factorial design, but I can´t understand why did Df, Sum Sq and Mean Sq of residuals alter when I Split the interaction? I think that Split the interaction must not alter the residuals. Am I doing something wrong? Could anyone help me? My data and functions I tried are: Y<-c(196,213,183, 192,253,199, 251,331,276,