boot.misclassMlogit {misclassGLM}

Compute Bootstrapped Standard Errors for misclassMlogit Fits

Description

Obtain bootstrapped standard errors.

Usage

boot.misclassMlogit(
  ret,
  Y,
  X,
  Pmodel,
  PX,
  boot.fraction = 1,
  repetitions = 1000
)

Arguments

ret

a fitted object of class inheriting from 'misclassMlogit'.

Y

a matrix of 0s and 1s, indicating the target class. This is the dependent variable.

X

a matrix containing the independent variables.

Pmodel

a fitted model (e.g. of class 'GLM' or 'mlogit') to implicitly produce variations of the predicted true values probabilities. (Usually conditional on the observed misclassified values and additional covariates.)

PX

covariates matrix suitable for predicting probabilities from Pmodel, usually including the mismeasured covariate.

boot.fraction

fraction of sample to be used for estimating the bootstrapped standard errors, for speedup.

repetitions

number of bootstrap samples to be drown.

See Also

misclassMlogit