[R] Plm function, error in uniqval[as.character(effect), , drop = F]
Hi, there,
I am trying to run a panel regression with a huge dataset, which has lots
of missing values. Here is some description of all variables.
> str(com3)
Classes ‘plm.dim’ and 'data.frame': 172153 obs. of 30 variables:
$ tic : Factor w/ 3435 levels "A","AA","AAC",..: 1 1 1 1 1
1 1 1 1 1 ...
$ idate : Factor w/ 81309 levels "2001/12/31 0:27",..: 34
2371 2450 4789 5977 7297 7650 9988 11288 12749 ...
$ IS_EFFECTIVE: int 1 1 1 1 1 1 1 1 1 1 ...
$ MATERIAL_WEAKNESS : int 0 0 0 0 0 0 0 0 0 0 ...
$ SIG_DEFICIENCY : int 0 0 0 0 0 0 0 0 0 0 ...
$ NOTEFF_ACC_RULE : int 0 0 0 0 0 0 0 0 0 0 ...
$ NOTEFF_FIN_FRAUD: int 0 0 0 0 0 0 0 0 0 0 ...
$ NOTEFF_OTHER: int 0 0 0 0 0 0 0 0 0 0 ...
$ IC_OP_TYPE_a1m0 : int NA NA NA NA NA NA NA NA NA NA ...
$ AUDITOR_FKEY: int NA NA NA NA NA NA NA NA NA NA ...
$ AUDITOR_AGREES : int NA NA NA NA NA NA NA NA NA NA ...
$ COMBINED_IC_OP : int NA NA NA NA NA NA NA NA NA NA ...
$ IC_IS_EFFECTIVE_Y1N0: Factor w/ 4 levels "","0","1","ND": NA NA NA NA NA
NA NA NA NA NA ...
$ AUDIT_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ NON_AUDIT_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ BENEFITS_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ IT_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ TAX_FEES: int NA NA NA NA NA NA NA NA NA NA ...
$ AUDIT_RELATED_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ OTHER_FEES : int NA NA NA NA NA NA NA NA NA NA ...
$ CARD: int NA NA NA NA NA NA NA NA NA NA ...
$ DISC: int NA NA NA NA NA NA NA NA NA NA ...
$ HACK: int NA NA NA NA NA NA NA NA NA NA ...
$ INSD: int NA NA NA NA NA NA NA NA NA NA ...
$ PHYS: int NA NA NA NA NA NA NA NA NA NA ...
$ PORT: int NA NA NA NA NA NA NA NA NA NA ...
$ STAT: int NA NA NA NA NA NA NA NA NA NA ...
$ UNKN: int NA NA NA NA NA NA NA NA NA NA ...
$ BRCH: int NA NA NA NA NA NA NA NA NA NA ...
$ ddate : Factor w/ 81306 levels "2001/12/31 0:27",..: 34
2371 2450 4789 5977 7297 7650 9988 11288 12749 ...
And I ran a panel regression as follow:
rm(list=ls())
library(plm)
como3 <- read.csv(file.path('como3.csv'),header = T, stringsAsFactors = F)
com3=plm.data(como3, indexes = NULL)
summary(com3)
Y <- cbind(com3$BRCH)
X <-
cbind(com3$IS_EFFECTIVE,com3$MATERIAL_WEAKNESS,com3$SIG_DEFICIENCY,com3$IC_IS_EFFECTIVE_Y1N0,com3$AUDITOR_AGREES,com3$COMBINED_IC_OP,com3$AUDIT_FEES)
fixed <- plm(Y ~ X,com3, index = c("tic","idate"),effect="individual",model
= "within")
summary(fixed)
Unfortunately, I got this error:
series IT_FEES, BRCH are constants and have been removedError in
uniqval[as.character(effect), , drop = F] :
incorrect number of dimensions
BRCH is my dependent variable, which is a dichotomous variable (happened
=1, unhappen=0). I don't know why it is considered as the "constant"? Does
it cause this error?
I have been looking for a solution in the internet for several days, but
have not found an answer to fix the problem.
Does anybody have an idea what I am doing wrong and what must be done to fix
the problem?
Thanks in advance.
Lynn Huang
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Re: [R] plm function & plm r.squared error
Dear Constanze,
the error message gives you a hint, where the problem might be. The
first error massage says that you have NAs in your index variables
"Unit" and "Week". You can check that with the is.na() function. The
second error message (r.squared) tells you to specify the model, that is
on which transformation of the data the R-squared has to be computed.
There is no default. Moreover, you insert a dataframe ("pCN04") instead
on a plm object in r.squared().
Kind regards
Nina Schönfelder
-
FernUniversität in Hagen
Fakultät für Wirtschaftswissenschaft
Lehrstuhl für Volkswirtschaftslehre,
insbes. Makroökonomik
58084 Hagen
On 16/02/15 22:25, fay constanze wrote:
DearGiovanni,Congratulationsfor the?truly helpful?plm package! Being new to R, I have a problem with the plm
function for financial markets timeseries data: After having defined a large, unbalanced panel pdata.frame
(https://www.dropbox.com/s/2r9t1cu9v65gobk/Database_CN_2004.csv?dl=0)and running a simple OLS model of two
variables regressing company returns(Perf) on index returns (PerfIn)synch <-plm (Perf ~ PerfIn , data=pCN04,
na.action = na.omit, index=c("Unit", "Week"), model="pooling") I keepreceiving the
following error:Error in model.matrix.pFormula(formula, data, rhs =1, model = model,? : ? NA in theindividual
index variableIn addition:Warning message:In `[.data.frame`(index, as.numeric(rownames(mf)),) :? NAsintroduced
by coercion
There aremuch more NAs in y (Perf) than in x (PerfIn) and I have tried to get rid ofthem
with na.omit. Another error I have is with the same model for the r.squaredfunction
r.squared(pCN04,model=NULL, Perf ~ PerfIn, type= "ess")Error in
tss.default(object, model = model) : ??unused argument (model = model)In addition:
Warning message:In mean.default(haty) : argument is not numeric or logical: returning
NAMany thanks in advance,your help is very precious to me!Constanze
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[R] plm function & plm r.squared error
DearGiovanni,Congratulationsfor the truly helpful plm package! Being new to R,
I have a problem with the plm function for financial markets timeseries data:
After having defined a large, unbalanced panel pdata.frame
(https://www.dropbox.com/s/2r9t1cu9v65gobk/Database_CN_2004.csv?dl=0)and
running a simple OLS model of two variables regressing company returns(Perf) on
index returns (PerfIn)synch <-plm (Perf ~ PerfIn , data=pCN04, na.action =
na.omit, index=c("Unit", "Week"), model="pooling") I keepreceiving the
following error:Error in model.matrix.pFormula(formula, data, rhs =1, model =
model, : NA in theindividual index variableIn addition:Warning message:In
`[.data.frame`(index, as.numeric(rownames(mf)),) : NAsintroduced by coercion
There aremuch more NAs in y (Perf) than in x (PerfIn) and I have tried to get
rid ofthem with na.omit. Another error I have is with the same model for the
r.squaredfunction r.squared(pCN04,model=NULL, Perf ~ PerfIn, type= "ess")Error
in tss.default(object, model = model) : unused argument (model = model)In
addition: Warning message:In mean.default(haty) : argument is not numeric or
logical: returning NAMany thanks in advance,your help is very precious to
me!Constanze
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[R] plm function
Dear Ieva,
plm(.., model="within") (which is the default for plm()) estimates a
within model on time-demeaned data, which is "equivalent" to using the
LSDV estimator. Therefore any time-constant dummy variable you add "by
hand" will be discarded because of perfect collinearity.
What kind of dummies are you trying to include? If they are
time-constant they will be incompatible with the within (FE) estimator,
but not with other uses of plm() like random effects ('model="random"')
or pooling ('model="pooling"').
A reproducible example, as requested by the posting guide, would have
clarified things.
Best wishes,
Giovanni
Giovanni Millo, PhD
Research Dept.,
Assicurazioni Generali SpA
Via Machiavelli 4,
34132 Trieste (Italy)
tel. +39 040 671184
fax +39 040 671160
- original message -
Message: 15
Date: Wed, 14 Mar 2012 13:46:03 +0200
From: Ieva Sriubait?
To: r-help@R-project.org
Subject: [R] plm function
Message-ID:
Content-Type: text/plain
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 estimate the statistics for those
dummy
variables?
Thank You.
Ieva
- end original message -
Ai sensi del D.Lgs. 196/2003 si precisa che le informazi...{{dropped:12}}
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] plm function
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 estimate the statistics for those dummy variables? Thank You. Ieva [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
