predict.mnprobit {switchSelection}

Predict method for mnprobit function

Description

Predict method for mnprobit function

Usage

## S3 method for class 'mnprobit'
predict(
  object,
  ...,
  newdata = NULL,
  alt = 1,
  regime = -1,
  type = ifelse(is.null(regime) | (regime == -1), "prob", "val"),
  alt_obs = "all",
  me = NULL,
  eps = NULL,
  control = list(),
  se = FALSE
)

Arguments

object

object of class "mnprobit"

...

further arguments (currently ignored)

newdata

an optional data frame in which to look for variables with which to predict. If omitted, the original data frame used. This data frame should contain values of dependent variables even if they are not actually needed for prediction (simply assign them with 0 values).

alt

index of the alternative. See 'Details' for more information.

regime

regime of the continuous equation. See 'Details' for more information.

type

string representing a type of prediction. See 'Details' for more information.

alt_obs

if alt_obs = "all" then all observations will be used for prediction. If alt_obs equals to the index of the alternative then only observations associated with this alternative will be used.

me

string representing the name of the variable for which marginal effect should be estimated. See 'Details' for more information.

eps

numeric vector of length 1 or 2 used for calculation of marginal effects. See 'Details'.

control

list of additional arguments. Currently is not intended for the users.

se

logical; if TRUE then the function also returns standard errors and p-values of the two-sided significance test associated with the function output. Works only if predict.mvoprobit returns numeric vector or a single column matrix. See delta_method for more information.

Details

See 'Examples' section of mnprobit for examples of this function application.

If type = "prob" then function returns a probability that alternative alt will be chosen. For example if alt = 2 then probabilities P(z_{i} = 2|w_{i}) will be estimated. If n_alt is null then the function returns a matrix such that i-th column contains probability of selecting i-th alternative.

If type = "li" then function returns a matrix which columns are linear indexes of corresponding equations.

If type = "val" then function returns predictions of conditional (on group) expectation of dependent variable in continuous equation with regimes determined by regime argument. To predict unconditional expectations just set alt = NULL.

If type = "lambda" then function returns conditional (on alt) expectation of random error of continuous equation in regime regime.

If me is provided then the function returns marginal effect of variable me respect to the statistic determined by type argument. For example if me = "x1" and type = "prob" then function returns a marginal effect of x1 on the corresponding probability i.e. one that would be estimated if me is NULL.

If length(eps) = 1 then eps is an increment in numeric differentiation procedure. If eps is NULL then this increment will be selected automatically taking into account scaling of variables. If length(eps) = 2 then marginal effects will be estimated as the difference between predicted value when variable me equals eps[2] and when it equals eps[1] correspondingly.

Value

This function returns predictions for each row of newdata or for each observation in the model if newdata is NULL. Structure of the output depends on the type argument (see 'Details' section).