MEregress: Generalized Maximum Entropy for estimating linear regression.

In woraphonyamaka/MEsreg: Generalized Maximum entropy for fitting smooth transition regression

Description

This function is used to estimate the linear gression model using GME.

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., Yamaka, W., & Sriboonchitta, S. (2019). Does the Kuznets curve exist in Thailand? A two decades’ perspective (1993–2015). Annals of Operations Research, 1-32.

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/MEsreg documentation built on April 11, 2021, 12:49 p.m.