copulaSampleSelObject: Fitted copulaSampleSel object
Description
A fitted semiparametric bivariate object returned by function copulaSampleSel and of class "copulaSampleSel" and "SemiParBIVProbit".Value
- fit
- List of values and diagnostics extracted from the output of the algorithm.
- gam1
- Univariate fit for equation 1. See the documentation of
mgcv for full details. - gam2, gam3, ...
- Univariate fit for equation 2, equation 3, etc.
- coefficients
- The coefficients of the fitted model.
- weights
- Prior weights used during model fitting.
- sp
- Estimated smoothing parameters of the smooth components.
- iter.sp
- Number of iterations performed for the smoothing parameter estimation step.
- iter.if
- Number of iterations performed in the initial step of the algorithm.
- iter.inner
- Number of iterations performed within the smoothing parameter estimation step.
- theta
- Estimated dependence parameter linking the two equations.
- n
- Sample size.
- X1, X2, X3, ...
- Design matrices associated with the linear predictors.
- X1.d2, X2.d2, X3.d2, ...
- Number of columns of
X1, X2, X3, etc. - l.sp1, l.sp2, l.sp3, ...
- Number of smooth components in the equations.
- He
- Penalized -hessian/Fisher. This is the same as
HeSh for unpenalized models. - HeSh
- Unpenalized -hessian/Fisher.
- Vb
- Inverse of
He. This corresponds to the Bayesian variance-covariance matrix
used for confidence/credible interval calculations. - t.edf
- Total degrees of freedom of the estimated bivariate model. It is calculated as
sum(diag(F)). - edf1, edf2, edf3, ...
- Degrees of freedom for the two equations of the fitted bivariate model (and for the third and fourth
equations if present. They
are calculated when splines are used.
- bs.mgfit
- List of values and diagnostics extracted from
magic in mgcv. - conv.sp
- If
TRUE then the smoothing parameter selection algorithm stopped before reaching the maximum number of iterations allowed. - wor.c
- Working model quantities.
- eta1, eta2, eta3, ...
- Estimated linear predictors for the two equations (as well as the third and fourth equations if present).
- y1, y2
- Responses of the two equations.
- logLik
- Value of the (unpenalized) log-likelihood evaluated at the (penalized or unpenalized) parameter
estimates.
- respvec
- List containing response vectors.