frm.ggoff is used to test the specification of fractional regression models.
an object containing the results of an
a vector containing the test versions to use. Available options:
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.ggoff may be used to test the link
specification of: (i) one-part fractional regression models; (ii) the binary
component of two-part fractional regression models; and (iii) the fractional
component of two-part fractional regression models. When the
version is implemented, it is taken into account the option that was chosen for
computing standard errors in the model under evaluation. For the
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 goodness-of-functional form test for binary and fractional regression models", Manchester School, 82(4), 488-507.
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N <- 250 u <- rnorm(N) X <- cbind(rnorm(N),rnorm(N)) dimnames(X)[] <- c("X1","X2") ym <- exp(X[,1]+X[,2]+u)/(1+exp(X[,1]+X[,2]+u)) y <- rbeta(N,ym*20,20*(1-ym)) 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 two-part fractional #regression model using a LR-based 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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