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J'effectue un test de Newey-West pour évaluer un estimateur d'une régression avec des résidus hétéroscédastiques et autocorrélés. J'utilise les paquets "sandwich" et "lmtest".R: Coeftest provoque une erreur
Alors que je peux facilement reproduire des exemples trouvés sur d'autres sites, mon propre script provoque l'erreur:
Erreur dans dimnames (cd) < - Liste (as.character (index (x)), colnames (x)): '' dimnames appliqués aux non-réseau
mon code:
ffregression <- lm(ex.return ~ fff$Mkt.RF + fff$SMB + fff$HML)
coeftest(ffregression,vcov=NeweyWest)
str (ffregression):
List of 12
$ coefficients : Named num [1:4] 0.00604 0.72976 0.90351 0.13548
..- attr(*, "names")= chr [1:4] "(Intercept)" "fff$Mkt.RF" "fff$SMB" "fff$HML"
$ residuals :An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34] -0.03637 0.0408 -0.00672 0.04648 -0.02275 ...
Indexed by objects of class: [yearmon] TZ:
Original class: 'double'
xts Attributes:
NULL
$ effects :An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34] -0.0606 0.1785 0.1379 0.0204 -0.0262 ...
Indexed by objects of class: [yearmon] TZ:
Original class: 'double'
xts Attributes:
NULL
$ rank : int 4
$ fitted.values:An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34] -0.000725 -0.031716 0.003868 0.051386 -0.047005 ...
Indexed by objects of class: [yearmon] TZ:
Original class: 'double'
xts Attributes:
NULL
$ assign : int [1:4] 0 1 2 3
$ qr :List of 5
..$ qr : num [1:34, 1:4] -5.831 0.171 0.171 0.171 0.171 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:34] "1" "2" "3" "4" ...
.. .. ..$ : chr [1:4] "(Intercept)" "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. ..- attr(*, "assign")= int [1:4] 0 1 2 3
..$ qraux: num [1:4] 1.17 1.05 1.14 1.14
..$ pivot: int [1:4] 1 2 3 4
..$ tol : num 1e-07
..$ rank : int 4
..- attr(*, "class")= chr "qr"
$ df.residual : int 30
$ xlevels : Named list()
$ call : language lm(formula = ex.return ~ fff$Mkt.RF + fff$SMB + fff$HML)
$ terms :Classes 'terms', 'formula' language ex.return ~ fff$Mkt.RF + fff$SMB + fff$HML
.. ..- attr(*, "variables")= language list(ex.return, fff$Mkt.RF, fff$SMB, fff$HML)
.. ..- attr(*, "factors")= int [1:4, 1:3] 0 1 0 0 0 0 1 0 0 0 ...
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:4] "ex.return" "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. .. .. ..$ : chr [1:3] "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. ..- attr(*, "term.labels")= chr [1:3] "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. ..- attr(*, "order")= int [1:3] 1 1 1
.. ..- attr(*, "intercept")= int 1
.. ..- attr(*, "response")= int 1
.. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
.. ..- attr(*, "predvars")= language list(ex.return, fff$Mkt.RF, fff$SMB, fff$HML)
.. ..- attr(*, "dataClasses")= Named chr [1:4] "nmatrix.1" "nmatrix.1" "nmatrix.1" "nmatrix.1"
.. .. ..- attr(*, "names")= chr [1:4] "ex.return" "fff$Mkt.RF" "fff$SMB" "fff$HML"
$ model :'data.frame': 34 obs. of 4 variables:
..$ ex.return :An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34, 1] -0.03709 0.00909 -0.00285 0.09786 -0.06975 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "RF"
Indexed by objects of class: [yearmon] TZ:
Original class: 'double'
xts Attributes:
NULL
..$ fff$Mkt.RF:An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34, 1] 0.0043 -0.0019 0.0206 0.0261 -0.0204 0.0424 -0.0197 0.0252 0.0255 -0.0006 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "Mkt.RF"
Indexed by objects of class: [yearmon] TZ:
xts Attributes:
NULL
..$ fff$SMB :An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34, 1] -0.0185 -0.0419 -0.0185 0.0301 -0.0422 0.004 -0.038 0.0428 -0.0205 0.0259 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "SMB"
Indexed by objects of class: [yearmon] TZ:
xts Attributes:
NULL
..$ fff$HML :An ‘xts’ object on Mar 2014/Dec 2016 containing:
Data: num [1:34, 1] 0.0503 0.011 -0.0036 -0.0066 -0.0002 -0.0055 -0.0119 -0.0168 -0.0298 0.0212 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr "HML"
Indexed by objects of class: [yearmon] TZ:
xts Attributes:
NULL
..- attr(*, "terms")=Classes 'terms', 'formula' language ex.return ~ fff$Mkt.RF + fff$SMB + fff$HML
.. .. ..- attr(*, "variables")= language list(ex.return, fff$Mkt.RF, fff$SMB, fff$HML)
.. .. ..- attr(*, "factors")= int [1:4, 1:3] 0 1 0 0 0 0 1 0 0 0 ...
.. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. ..$ : chr [1:4] "ex.return" "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. .. .. .. ..$ : chr [1:3] "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. .. ..- attr(*, "term.labels")= chr [1:3] "fff$Mkt.RF" "fff$SMB" "fff$HML"
.. .. ..- attr(*, "order")= int [1:3] 1 1 1
.. .. ..- attr(*, "intercept")= int 1
.. .. ..- attr(*, "response")= int 1
.. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
.. .. ..- attr(*, "predvars")= language list(ex.return, fff$Mkt.RF, fff$SMB, fff$HML)
.. .. ..- attr(*, "dataClasses")= Named chr [1:4] "nmatrix.1" "nmatrix.1" "nmatrix.1" "nmatrix.1"
.. .. .. ..- attr(*, "names")= chr [1:4] "ex.return" "fff$Mkt.RF" "fff$SMB" "fff$HML"
- attr(*, "class")= chr "lm"
Exemple:
set.seed(04012017)
n<-34
correlated_residuals<-arima.sim(list(ar = .9), n)
y<-correlated_residuals
x<-1:n
plot(x,correlated_residuals)
fit<-lm(y~x)
abline(fit)
summary(fit) # standard estimates
coeftest(fit,vcov=NeweyWest(fit,verbose=T))
str (TRG):
List of 12
$ coefficients : Named num [1:2] -0.179 0.148
..- attr(*, "names")= chr [1:2] "(Intercept)" "x"
$ residuals : Named num [1:34] -0.9529 0.976 0.3025 -0.0486 -1.1214 ...
..- attr(*, "names")= chr [1:34] "1" "2" "3" "4" ...
$ effects : Named num [1:34] -14.026 8.449 0.25 -0.085 -1.142 ...
..- attr(*, "names")= chr [1:34] "(Intercept)" "x" "" "" ...
$ rank : int 2
$ fitted.values: Named num [1:34] -0.0314 0.1163 0.264 0.4116 0.5593 ...
..- attr(*, "names")= chr [1:34] "1" "2" "3" "4" ...
$ assign : int [1:2] 0 1
$ qr :List of 5
..$ qr : num [1:34, 1:2] -5.831 0.171 0.171 0.171 0.171 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:34] "1" "2" "3" "4" ...
.. .. ..$ : chr [1:2] "(Intercept)" "x"
.. ..- attr(*, "assign")= int [1:2] 0 1
..$ qraux: num [1:2] 1.17 1.23
..$ pivot: int [1:2] 1 2
..$ tol : num 1e-07
..$ rank : int 2
..- attr(*, "class")= chr "qr"
$ df.residual : int 32
$ xlevels : Named list()
$ call : language lm(formula = y ~ x)
$ terms :Classes 'terms', 'formula' language y ~ x
.. ..- attr(*, "variables")= language list(y, x)
.. ..- attr(*, "factors")= int [1:2, 1] 0 1
.. .. ..- attr(*, "dimnames")=List of 2
.. .. .. ..$ : chr [1:2] "y" "x"
.. .. .. ..$ : chr "x"
.. ..- attr(*, "term.labels")= chr "x"
.. ..- attr(*, "order")= int 1
.. ..- attr(*, "intercept")= int 1
.. ..- attr(*, "response")= int 1
.. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
.. ..- attr(*, "predvars")= language list(y, x)
.. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
.. .. ..- attr(*, "names")= chr [1:2] "y" "x"
$ model :'data.frame': 34 obs. of 2 variables:
..$ y: num [1:34] -0.984 1.092 0.566 0.363 -0.562 ...
..$ x: int [1:34] 1 2 3 4 5 6 7 8 9 10 ...
..- attr(*, "terms")=Classes 'terms', 'formula' language y ~ x
.. .. ..- attr(*, "variables")= language list(y, x)
.. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
.. .. .. ..- attr(*, "dimnames")=List of 2
.. .. .. .. ..$ : chr [1:2] "y" "x"
.. .. .. .. ..$ : chr "x"
.. .. ..- attr(*, "term.labels")= chr "x"
.. .. ..- attr(*, "order")= int 1
.. .. ..- attr(*, "intercept")= int 1
.. .. ..- attr(*, "response")= int 1
.. .. ..- attr(*, ".Environment")=<environment: R_GlobalEnv>
.. .. ..- attr(*, "predvars")= language list(y, x)
.. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
.. .. .. ..- attr(*, "names")= chr [1:2] "y" "x"
- attr(*, "class")= chr "lm"
C'était le problème, merci Paul! – user169340