Displaying 20 results from an estimated 200 matches similar to: "about the pgmm in plm package (application and singularity)"
2009 Mar 30
0
pgmm (Blundell-Bond) sample needed)
Dear Ivo, dear list,
(see: Message: 70
Date: Thu, 26 Mar 2009 21:39:19 +0000
From: ivowel at gmail.com
Subject: [R] pgmm (Blundell-Bond) sample needed)
I think I finally figured out how to replicate your supersimple GMM
example with pgmm() so as to get the very same results as Stata.
Having no other regressors in the formula initially drove me crazy. This was a case where simpler models are
2010 Mar 13
0
PGMM help - Strange Errors when Fitting Models
Hello,
I've been trying to fit Arrellano-Bond model with pgmm but I am getting very
strange errors. I've looked around and found no reference to them.
I've specified the model in dozens of different ways, and each seems to give
me a new kind of error. This leads me to believe this has to do with the
way the data is specified, but I can't see anything thats wrong with. My
2012 Apr 09
0
Error using PGMM function in the PLM package
Good day fellow R users:
I have routinely received the following message when attempting to
estimate a GMM model for a somewhat square panel (N = 20, T = 9-27,
Obs = 338) using the pgmm function in the plm package:
Error in function (..., deparse.level = 1) :
number of rows of matrices must match (see arg 2)
So far, I am not wedded to a particular GMM model but what I have used
thus far is
2009 Mar 26
1
pgmm (Blundell-Bond) sample needed
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,
2009 Mar 08
1
singular matrices in plm::pgmm()
Hi list,
has anyone succeeded in using pgmm() on any dataset besides
Arellano/Bond's EmplUK, as shown in the vignette?
Whatever I try, I eventually get a runtime error because of a singular
matrix at various points in pgmm.diff() (which gets called by pgmm()).
For example, when estimating a "dynamic" version of the Grunfeld data:
data(Grunfeld, package="Ecdat")
grun
2009 Mar 27
0
R: plm and pgmm
dear giovanni---
thanks for answering on r-help to me as well as privately. I very much
appreciate your responding. I read the plm vignette. I don't have the book,
so I can't consult it. :-(. I am going to post this message now (rather
than just email it privately), because other amateurs may have similar
questions in the future, and find this message and your answers via google.
2010 Jun 26
0
dynamic panelmodel pgmm
Hi,
I want to estimate a dynamic paneldata model with the following code, but unfortenately I received the error message below.
form<-PB~Activity+Solvency+Cap_Int
2012 Nov 09
0
Can pgmm in the plm package include additional endogenous variables?
Dear R-Users,
I am using pgmm in the plm package to estimate a dynamic models with panel
data. Besides the lagged dependent variable, I also have some other
endogenous variables. Does the pgmm have an argument that allows me to
specify these endogenous variables and their instruments? I didn't find this
argument in the description and online.
Thank you very much for your help!
2017 Dec 25
1
package : plm : pgmm question
Dear Sir,
I am using the package pgmm you build in panel regression. However, I found that when T is 10, N=30, the error would show as following:
system is computationally singular: reciprocal condition number
But the similar code works well on Stata, so I wonder how I can optimize the algorithm, for example , the inverse matrix optimization ? And I have checked my data as well, no
2013 May 07
0
Orthogonal transformation option in pgmm-plm
Hi,
I'm a pgmm (plm) user and would like to know if a orthogonal transformation
is available, as in Stata xtabond2. Can someone help me? Thanks! Kinds
regards,
Eva
[[alternative HTML version deleted]]
2010 May 17
0
(no subject)
Dear Limin,
might be just about anything. Could you please provide a reproducible
example?
Best,
Giovanni
----------------- Original message ----------------------
Message: 51
Date: Mon, 17 May 2010 10:36:03 +0800 (CST)
From: ??? <dlmsos at 163.com>
To: r-help at r-project.org
Subject: [R] pgmm function
Message-ID: <b2cba0.35fc.128a41e3684.Coremail.dlmsos at 163.com>
Content-Type:
2011 Jun 12
3
Running a GMM Estimation on dynamic Panel Model using plm-Package
Hello,
although I searched for a solution related to my problem I didn?t find one,
yet. My skills in R aren?t very large, however.
For my Diploma thesis I need to run a GMM estimation on a dynamic panel
model using the "pgmm" - function in the plm-Package.
The model I want to estimate is: "Y(t) = Y(t-1) + X1(t) + X2(t) + X3(t)" .
There are no "normal" instruments
2013 Jan 13
1
R error: system is computationally singular when building GMM model
Dear,
I built the generalized method of moments model to estimate the sales rank
in the bookstore using plm package in R.
The equation is:
data1.gmm <- pgmm(dynformula(lnsales_rank ~ ln_price + avg_ham_rate +
avg_spam_rate + num_of_ham+ num_of_spam + ship_code2 +ship_code3
+ship_code4+ ship_code5+ ship_code6 + ship_ code7, lag = list(0, 0, 0,
0,0,0,0,0,0,0,0,0), log =FALSE), data=data,
2010 Aug 02
0
(no subject)
Dear Hao-pang,
it is impossible to really tell the problem without a reproducible
example. Just guessing: this looks like you have too many regressors.
In GMM, lags of variables are used as instruments, so you might have
more regressors than observations. Try reducing the 'lag' argument
(which, by default, uses all lags available).
Of course, the first observation to make would be that
2013 Feb 28
0
GMM for dynamic mdels: what if never passes Sargan test?
Hi! I am looking for some insight with this situation: what to do or how to
analyze when our models fitted with pgmm never pass Sargant test?
With my current dataset, I've been fitting different models and with all
possible combinations of lagged instruments, with all possible lag order
combinations, but no model passes Sargan test. I can not give up gmm here
as I have autocorrelation and
2013 Mar 05
2
Issues when using interaction term with a lagged variable
Hi there!
Today I tried to estimate models using both plm and pgmm functions, with an
interaction between X1 and lag(X2, 1). And I notice two issues.
Let "Y=b_1 * X_1 + b_2 * X_2 + b_3 * X_1 * x_2 + e" be our model.
1) When using plm, I got different results when I coded the interaction
term with I(X1 * lag(X2, 1)) and when I just saved this multiplication X1 *
lag(X2, 1) in a
2001 Apr 16
1
Nesticle
Presumably you *know* it was working because of my screenshots page, so
I'll answer :)
The upshot is Nesticle got broken when the TransGaming stuff started
landing in December. The basic problem is that the new code was for
DirectX7, while Nesticle is a DX5 app. I believe there's been some work
to fix that - I'll check latest CVS later today.
--
Ian Schmidt - ischmidt [at]
2009 Apr 01
0
回复: R-help Digest, Vol 73, Issue 32
Dear sir, How to do bilinear time series in R?Is there any functions or packages? thank you!
-----Sincerely yours
Kuangnan Fang 方匡南 敬上
department of statistics ,Economics school,Xia men University.
Fujian Province (361005) China
Mobile Phone:15860721915 SKYPE: ruiqwy
MSN Messenger: ruiqwy@hotmail.com
QQ:39863401
--- 09年3月31日,周二, r-help-request@r-project.org
2009 Feb 14
2
Dynamic Panel Analysis in R
Hi!
I am quite a new user of R. I wanted to ask if there was some package
for dynamic panel analysis (with Arneallo-Bond Method) like stata. PLM
is for panel analysis but not for dynamic.
Best regards,
Tanveer
2008 Dec 19
2
How do I generate one vector for every row of a data frame?
I am trying to generate a set of data points from a Gaussian mixture
model. My mixture model is represented by a data frame that looks
like this:
> gmm
weight mean sd
1 0.3 0 1.0
2 0.2 -2 0.5
3 0.4 4 0.7
4 0.1 5 0.3
I have written the following function that generates the appropriate data:
gmm_data <- function(n, gmm) {
c(rnorm(n*gmm[1,]$weight, gmm[1,]$mean,