Implements generalized maximum entropy estimation for linear regression,
kink regression, and smooth transition kink regression models. The approach
represents unknown parameters and disturbances as probability distributions
over discrete support spaces and estimates them by maximizing entropy subject
to model constraints. It is particularly suited to ill-posed problems and does
not require distributional assumptions on the error term. The methods have been
applied in empirical studies such as Tarkhamtham and Yamaka (2019)
< https://thaijmath.com/index.php/thaijmath/article/view/867/870> and Maneejuk, Yamaka, and Sriboonchitta (2022)
#To install this package, you have to install devtools package
library(devtools)
install_github("woraphonyamaka/MEsreg", force=TRUE)
library(MEsreg)