On 2020-07-09 07:15 -0700, Bert Gunter wrote:
> On Thu, Jul 9, 2020 at 3:09 AM Valerio Leone Sciabolazza
> wrote:
> >
> > When calculating a panel data
> > regression with multiple fixed
> > effects using the function felm()
> > from the lfe package, no constant
> > term (i.e. intercept) is
While you may get lucky here, your experience on SO indicates that you may
do better by contacting the package maintainer (?maintainer) and asking
him/her to refer you to appropriate references, as this sounds like a
statistical methodology query.
Bert Gunter
"The trouble with having an open mind
Dear list users,
When calculating a panel data regression with multiple fixed effects
using the function felm() from the lfe package, no constant term (i.e.
intercept) is generated in the summary results.
In an old post on stackoverflow [1], someone suggested that it is
possible to retrieve the va
Dear All,
I am trying to implement a regression with state-specific trends in R. I
can implement this in Stata with ease, but I am hoping to preserve my R
workflow. I suspect there is an "R formula trick" that I'm just not
understanding and I would be grateful to anyone who could help me
understan
> since the OLS and robust regressions have the same number of DFs, looking
> at the residual standard error is insightful.
Sadly not. The residual scale in a robust model is only partly indicative of
goodness of fit; robust models intentionally downweight outliers. Much of the
difference in
On Tue, May 19, 2015 at 1:23 PM, michael westphal via R-help
wrote:
You can't compare them (statistically -- you can of course draw
pictures). Note, from ?rlm:
" Note that the df.residual component is deliberately set to NA to
avoid inappropriate estimation of the residual scale from the residua
Hello:
I am using R 3.0.2.
I have panel data on countries' renewable energy net generation (and installed
capacity) over time. I am regressing these dependent variables on various
socioeconomic variables, as well as binary policy variables. I have have done
basic OLS, but I wanted to explore
the regression.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Roy Lowrance
Sent: Sunday, March 21, 2010 8:01 PM
To: r-help@r-project.org
Subject: [R] fixed effects regression
Hi All:
I am trying to move a model from Stata to R.
It
The 90,000 indicators are the interactions between 300 zip codes (= postal
codes) and 300 month indices.
- Roy
On Mon, Mar 22, 2010 at 5:56 AM, Petr PIKAL wrote:
> Hi
>
> r-help-boun...@r-project.org napsal dne 22.03.2010 01:01:00:
>
> > Hi All:
> >
> > I am trying to move a model from Stata to
Hi All:
I am trying to move a model from Stata to R.
It is a linear regression model with about 90,000 indicator variables.
What is the best approach to follow in R?
- Roy
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing
: untested code.
Bill Venables.
Bill Venables
http://www.cmis.csiro.au/bill.venables/
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of parkbomee
Sent: Saturday, 7 February 2009 1:57 PM
To: r-help@r-project.org
Subject: [R] fixed effec
Hi everyone,
I am running this fixed effects model in R.
The thing is, my own code and the canned routine keep returning different
estimates for the fixed effects factors and intercept.
(The other variables' estimates and R^2 are the same!!! weird!!)
I attach my own code, just in case.
I am pre
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