Kinkreg1 | R Documentation |
The least sqaure estimation of kink regression model without exogenous varible
Kinkreg1(y,x,Call="optim")
y |
the vector of dependent variable |
x |
the matrix of regime-dependent independent variable |
Call |
if Call="optim" == optimization if Call="residuals" == retrun the residul series |
The kink regression model without exogenous variable is the nonlinear model in which the continous function is change at the kink point.
Result |
the parameter estimates, standard error, t-stat and p-value |
RSS |
Residual sum Sqaures |
Woraphon Yamaka
Hansen, B. E. (2017). Regression kink with an unknown threshold. Journal of Business & Economic Statistics, 35(2), 228-240.
Sriboochitta, S., Yamaka, W., Maneejuk, P., & Pastpipatkul, P. (2017). A generalized information theoretical approach to non-linear time series model. In Robustness in Econometrics (pp. 333-348). Springer, Cham.
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., & Yamaka, W. (2020). An analysis of the impacts of telecommunications technology and innovation on economic growth. Telecommunications Policy, 44(10), 102038.
Maneejuk, P., & Yamaka, W. (2021). The Impact of Higher Education on Economic Growth in ASEAN-5 Countries. Sustainability, 13(2), 520.
#### Example Simulation data set.seed(111) # Set seed for reproducibility k = 1 #number of dependent variable n = 500 #number of observation r1=1.5 # Kink parameter x = matrix(rnorm(n*k,r1,2),ncol=k) e = rnorm(n,0,sd=1) x1 = cbind(neg.part(x-r1),pos.part(x-r1)) y=0.5+(0.5*x1[,1])-(1*x1[,2])+e plot(x,y, col="red", lwd=2) Kinkreg1(y,x,Call="optim")
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