MEregress: Generalized Maximum Entropy for estimating linear regression.

In woraphonyamaka/GMEreg: Generalized Maximum Entropy regression

Usage

MEregress(y,x,number,Z,V)

Arguments

y	dependent variable
x	One dimension of dependent variable
number	number of supports i.e. "3", "5" and "7
Z	bound of coefficient
V	bound of error

Details

This funciton is used to estimated the linear regression

Value

beta	intercept,beta
Maxent	Maximum entropy

Author(s)

Dr.Woraphon Yamaka

References

Golan, A., Judge, G. G., & Miller, D. (1996). Maximum entropy econometrics. Iowa State University, Department of Economics. Jaynes, E. T. (1957). Information theory and statistical mechanics. Physical review, 106(4), 620.

Maneejuk, P. and Yamaka, W. (2020). Entropy Inference in Smooth Transition Kink Regression

Examples

library("Rsolnp")
set.seed(1)
n=100
e=rnorm(n)
x0=rnorm(n)
x1=rnorm(n)
y=1+2*x0+3*x1+e
x=cbind(x0,x1)
MEregress(y,x,number="3",Z=10,V=5)

woraphonyamaka/GMEreg documentation built on July 28, 2020, 9:59 a.m.