coef.mvoprobit {switchSelection}R Documentation

Coefficients extraction method for mvoprobit.

Description

Extract coefficients and other estimates from mvoprobit object.

Usage

## S3 method for class 'mvoprobit'
coef(object, ..., eq = NULL, eq2 = NULL, regime = NULL, type = "coef")

Arguments

object

object of class "mvoprobit".

...

further arguments (currently ignored).

eq

integer representing an index of the ordered equation.

eq2

integer representing an index of the continuous equation.

regime

integer representing a regime of the continuous equation.

type

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.

Details

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.

Value

See 'Details' section.


[Package switchSelection version 1.1.2 Index]