Extract coefficients and other estimates from mvoprobit object.
# S3 method for mvoprobit
coef(object, ..., eq = NULL, eq2 = NULL, regime = NULL, type = "coef")See 'Details' section.
object of class "mvoprobit".
further arguments (currently ignored).
integer representing an index of the ordered equation.
integer representing an index of the continuous equation.
integer representing a regime of the continuous equation.
character representing a type of the output. Possible options
are "coef", "coef2", "cov", "cov1", "var",
"cov2", "cov3", coef_lambda and marginal.
See 'Details' for additional information.
Consider notations from the 'Details' section of
mvoprobit.
Suppose that type = "coef". Then estimates of \(\gamma_{j}\)
coefficients are returned for each \(j\in\{1,...,J\}\).
If eq = j then only estimates of \(\gamma_{j}\) coefficients
are returned.
Suppose that type = "coef_var". Then estimates of \(\gamma_{j}^{*}\)
coefficients are returned for each \(j\in\{1,...,J\}\).
If eq = j then only estimates of \(\gamma_{j}^{*}\) coefficients
are returned.
Suppose that type = "coef2". Then estimates of \(\beta_{r}\)
coefficients are returned for each \(r\in\{0,...,R - 1\}\).
If eq2 = k then only estimates for the \(k\)-th continuous equation
are returned. If regime = r then estimates of \(\beta_{r}\)
coefficients are returned for the eq2-th continuous equation.
Herewith if regime is not NULL and eq2 is NULL
it is assumed that eq2 = 1.
Suppose that type = "cov". Then estimate of the asymptotic covariance
matrix of the estimator is returned. Note that this estimate depends
on the cov_type argument of mvoprobit.
Suppose that type = "cov1". Then estimate of the covariance matrix of
\(u_{i}\) is returned. If eq = c(a, b) then the function returns
\((a, b)\)-th element of this matrix i.e. an element from
a-th row and b-th column.
Suppose that type = "cov12". Then estimates of covariances between
\(u_{i}\) and \(\varepsilon_{i}\) are returned. If eq2 = k then
covariances with random errors of the k-th continuous equation are
returned. If in addition eq = j and regime = r then the
function returns estimate of \(Cov(u_{ji}, \varepsilon_{ri})\) for the
k-th equation. If eq2 = NULL it is assumed that
eq2 = 1.
Suppose that type = "var" or type = "cov2". Then estimates of
the variances of \(\varepsilon_{i}\) are returned. If eq2 = k
then estimates only for \(k\)-th continuous equation are returned.
If in addition regime = r then estimate of \(Var(\varepsilon_{ri})\)
is returned. Herewith if regime is not NULL and
eq2 is NULL it is assumed that eq2 = 1.
Suppose that type = "cov3". Then estimates of the covariances between
random errors of different equations in different regimes are returned.
If eq2 = c(a, b) and regime = c(c, d) then function returns
an estimate of the covariance of random errors of the
a-th and b-th
continuous equations in regimes c and d correspondingly.
If this covariance is not identifiable then NA value is returned.
Suppose that type = "coef_lambda". Then estimates of the coefficients
for \(\hat{\lambda}^{t}_{ji}\) are returned i.e.
estimates of \(\tau_{jt}\) for each regime.
If regime = r then estimates are returned for the \(r\)-th
regime. If in addition eq = j then only estimates for this \(j\)
are returned.