summary.optimrml: Summary method for class 'optimrml'

In BiProbitPartial: Bivariate Probit with Partial Observability

Description

Summary method for class 'optimrml'

Usage

## S3 method for class 'optimrml'
summary(object, ...)

Arguments

object	Object of class optimrml
...	unused

Value

matrix summary of estimates. The columns are

Estimate

Maximum likelihood point estimate

Std. Error

Asymptotic standard error estimate of maximum likelihood point estimators using numerical hessian

z value

z value for zero value null hypothesis using asymptotic standard error estimate

Pr(>|z|)

P value for a two sided null hyptothesis test using the z value

Examples

data('Mroz87',package = 'sampleSelection')
Mroz87$Z = Mroz87$lfp*(Mroz87$wage >= 5)

f1 = BiProbitPartial(Z ~ educ + age + kids5 + kids618 + nwifeinc | educ + exper + city, 
     data = Mroz87, philosophy = "frequentist")
summary(f1)

b1 = BiProbitPartial(Z ~ educ + age + kids5 + kids618 + nwifeinc | educ + exper + city, 
    data = Mroz87, philosophy = "bayesian", 
    control = list(beta = f1$par[1:(length(f1$par)-1)], rho = tail(f1$par,1)))
summary(b1)

BiProbitPartial documentation built on May 2, 2019, 1:48 p.m.