similar to: plm – tests of poolability – error: insufficient number of observations

Hello Cecilia, nice hearing from you again. I must restate a couple of my old hints, though ;^) 1) please always put the authors c/c, as we are not guaranteed to browse through the r-help every day 2) please provide reproducible examples. As example(pooltest) keeps working fine, as do some other cases I tried (Grunfeld data etc.), I don't know what the problem is but evidently your data are

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 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

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

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 All, I am doing econometric modeling of panel data (fixed effects). We currently use Eviews to do this, but I have discovered a bug in Eviews 7 and am exploring the use of R to build panel data models / longitudinal data models. I looked at the plm package but do not see how I can incorporate AR terms in the model using the plm package. I have an Eviews model with two AR terms, AR(1) and

Just a general question concerning the woolf test (package vcd), when we have stratified data (2x2 tables) and when the p.value of the woolf-test is below 0.05 then we assume that there is a heterogeneity and a common odds ratio cannot be computed? Does this mean that we have to try to add more stratification variables (stratify more) to make the woolf-test p.value insignificant? Also in the

When running R CMD check on a package, we are encountering an error on R-devel (as of 72457) on Linux. Unfortunately, it is very hard to reproduce, and almost any change to the code makes the error go away. I believe that this is due to a bug in R-devel, which has been present since at least commit 72128 (on 2017-02-06). The test error occurs when R CMD check is run on Travis CI (on Ubuntu

El 18 de noviembre de 2020 15:16:09 GMT-05:00, Rowland penny via samba <samba at lists.samba.org> escribi?: >On 18/11/2020 19:27, Rommel Rodriguez Toirac wrote: >> >> ?It is /etc/named.conf and /etc/samba/smb.conf >> >> >> # cat /etc/named.conf >> >> >> ??tkey-gssapi-keytab "/usr/local/samba/private/dns.keytab"; >> >>

Hi R-help, I am working with US COOP network station data and the files are concatenated in single rows for all years, but I need to pull these apart into rows for each day. To do this, I need to extract part of each row such as station id, year, mo, and repeat this against other variables in the row (days). My problem is that there are repeated values for each day, and the files are fixed width

Note that one of the 8 patches (#6) will be sent separately in reply to this email, as some of the replaced lines are too long, so git won't let me send the email. However, there is nothing wrong with that patch, and it should be applied in the sequence listed below. Note also that I assume this will be tested on a clean f11 install, rather than an upgrade of an existing ovirt server