Description Usage Arguments Details Value Author(s) References See Also Examples
frm.ggoff
is used to test the specification of fractional regression models.
1 
object 
an object containing the results of an 
version 
a vector containing the test versions to use. Available options: 
table 
a logical value indicating whether a summary table with the test results should be printed. 
... 
Arguments to pass to glm, which is used to estimate the model under the alternative hypothesis when

frm.ggoff
applies the GGOFF, GOFF1 and GOOFF2 test statistics to fractional regression
models estimated via frm
. frm.ggoff
may be used to test the link
specification of: (i) onepart fractional regression models; (ii) the binary
component of twopart fractional regression models; and (iii) the fractional
component of twopart fractional regression models. When the Wald
version is implemented, it is taken into account the option that was chosen for
computing standard errors in the model under evaluation. For the LM
version,
a robust version is computed in cases (i) and (iii) and a conventional version in
case (ii). See Ramalho, Ramalho and Murteira (2014) for details on the application of the
GGOFF, GOFF1 and GOOFF2 tests in the fractional regression framework.
frm.ggoff
returns a named vector with the test results.
Joaquim J.S. Ramalho <[email protected]>
Ramalho, E.A., J.J.S. Ramalho and J.M.R. Murteira (2014), "A generalized goodnessoffunctional form test for binary and fractional regression models", Manchester School, 82(4), 488507.
frm
, for fitting fractional regression models.
frm.reset
, for asymptotically equivalent specification tests.
frm.ptest
, for nonnested hypothesis tests.
frm.pe
, for computing partial effects.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  N < 250
u < rnorm(N)
X < cbind(rnorm(N),rnorm(N))
dimnames(X)[[2]] < c("X1","X2")
ym < exp(X[,1]+X[,2]+u)/(1+exp(X[,1]+X[,2]+u))
y < rbeta(N,ym*20,20*(1ym))
y[y > 0.9] < 1
#Testing the logit specification of a standard fractional regression model
#using LM and Wald versions of the GGOFF test, based on 1 or 2 fitted powers of
#the linear predictor
res < frm(y,X,linkfrac="logit",table=FALSE)
frm.ggoff(res,c("Wald","LM"))
#Testing the probit specification of the binary component of a twopart fractional
#regression model using a LRbased GGOFF test
res < frm(y,X,linkbin="probit",type="2Pbin",inf=1,table=FALSE)
frm.ggoff(res,"LR")
## See the website http://evunix.uevora.pt/~jsr/FRM.htm for more examples.

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