basepredict.tobit: predicted value

In benjaminschlegel/glm.predict: Predicted Values and Discrete Changes for Regression Models

predicted value

Description

The function calculates the predicted value with the confidence interval for a tobit model.

Usage

## S3 method for class 'tobit'
basepredict(model, values, sim.count=1000, conf.int=0.95, sigma=NULL, set.seed=NULL,
  type = c("any", "simulation", "bootstrap"), summary = TRUE)

Arguments

model	the model Object generated with tobit()
values	the values of the case as vector in the order how they appear in the summary(model) Estimate
sim.count	OPTIONAL numbers of simulations to be done by the function. default: 1000
conf.int	OPTIONAL the confidence interval used by the function. default: 0.95
sigma	OPTIONAL the variance-covariance matrix, can be changed when having for example robust or clustered vcov. default: vcov(model)
set.seed	OPTIONAL set a seed for the random number generator
type	OPTIONAL only simulation is supported for tobit()
summary	OPTIONAL if mean/quantiles should be return or all simulated values (default: TRUE)

Details

The function makes a simulation for the two cases and compares them to each other.

Value

The output is a 3x3 matrix having in the first column the predicted value, in the second column the lower value of the confidence interval and in the third column the upper value of the confidence interval.

Author(s)

Benjamin Schlegel, [e-mail]

Examples

library(AER)
model1 = tobit(Age ~ Height + Pulse, right = 65, data=MASS::survey)
summary(model1)
# Person with a height of 160 and a pulse of 80
basepredict(model1, values = c(1,160,80))

benjaminschlegel/glm.predict documentation built on March 18, 2024, 6:46 a.m.