| encomptest {lmtest} | R Documentation |
encomptest performs the encompassing test of Davidson & MacKinnon
for comparing non-nested models.
encomptest(formula1, formula2, data = list(), vcov. = NULL, ...)
formula1 |
either a symbolic description for the first model to be tested,
or a fitted object of class |
formula2 |
either a symbolic description for the second model to be tested,
or a fitted object of class |
data |
an optional data frame containing the variables in the
model. By default the variables are taken from the environment
which |
vcov. |
a function for estimating the covariance matrix of the regression
coefficients, e.g., |
... |
further arguments passed to |
To compare two non-nested models, the encompassing test fits an encompassing
model which contains all regressors from both models such that the two
models are nested within the encompassing model. A Wald test for comparing
each of the models with the encompassing model is carried out by waldtest.
For further details, see the references.
An object of class "anova" which contains the residual degrees of freedom
in the encompassing model, the difference in degrees of freedom, Wald statistic
(either "F" or "Chisq") and corresponding p value.
R. Davidson & J. MacKinnon (1993). Estimation and Inference in Econometrics. New York, Oxford University Press.
W. H. Greene (1993), Econometric Analysis, 2nd ed. Macmillan Publishing Company, New York.
W. H. Greene (2003). Econometric Analysis, 5th ed. New Jersey, Prentice Hall.
## Fit two competing, non-nested models for aggregate
## consumption, as in Greene (1993), Examples 7.11 and 7.12
## load data and compute lags
data(USDistLag)
usdl <- na.contiguous(cbind(USDistLag, lag(USDistLag, k = -1)))
colnames(usdl) <- c("con", "gnp", "con1", "gnp1")
## C(t) = a0 + a1*Y(t) + a2*C(t-1) + u
fm1 <- lm(con ~ gnp + con1, data = usdl)
## C(t) = b0 + b1*Y(t) + b2*Y(t-1) + v
fm2 <- lm(con ~ gnp + gnp1, data = usdl)
## Encompassing model
fm3 <- lm(con ~ gnp + con1 + gnp1, data = usdl)
## Cox test in both directions:
coxtest(fm1, fm2)
## ...and do the same for jtest() and encomptest().
## Notice that in this particular case they are coincident.
jtest(fm1, fm2)
encomptest(fm1, fm2)
## the encompassing test is essentially
waldtest(fm1, fm3, fm2)