| Type: | Package |
| Version: | 0.1.0 |
| Title: | Regression Kink with a Time-Varying Threshold |
| Description: | An algorithm is proposed to estimate regression kink model proposed by the paper, Lixiong Yang and Jen-Je Su (2018) <doi:10.1016/j.jimonfin.2018.06.002>. |
| Imports: | MASS |
| Depends: | R (≥ 3.5.0) |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.1 |
| Author: | Lixiong Yang [aut, cre] |
| Maintainer: | Lixiong Yang <ylx@lzu.edu.cn> |
| NeedsCompilation: | no |
| Packaged: | 2021-04-13 07:58:25 UTC; ylx |
| Repository: | CRAN |
| Date/Publication: | 2021-04-15 07:30:06 UTC |
negtive part of a variable
Description
This is a function computing the negtive part of a variable.
Usage
neg.part(x)
Arguments
x |
A vector of response. |
Value
ne |
The negative part of a variable. |
Examples
pt1 <- proc.time()
##Simulated data
set.seed(12345)
n=200
x = rnorm(n)
obj <- neg.part(x)
proc.time() - pt1
positive part of a variable
Description
This is a function computing the positive part of a variable.
Usage
pos.part(x)
Arguments
x |
A vector of response. |
Value
ps |
The positive part of a variable. |
Examples
pt1 <- proc.time()
##Simulated data
set.seed(12345)
n=200
x = rnorm(n)
obj <- pos.part(x)
proc.time() - pt1
linear regression
Description
This is a function computing OLS estimates of linear model.
Usage
reg(X,y)
Arguments
y |
A vector of response. |
X |
data matrix |
Value
bols |
The ols estimates of a linear regression model. |
Examples
pt1 <- proc.time()
##Simulated data
set.seed(12345)
n=200
e = rnorm(n)
X = cbind(1,rnorm(n))
b0 =c(1,2)
y = X
obj <- reg(X,y)
proc.time() - pt1
Estimation for regression kink with a time-varying threshold
Description
This is a function estimating regression kink with a time-varying threshold.
Usage
rkt(y,x,z,q,r01,r02,r11,r12,stp1,stp2)
Arguments
y |
A vector of response. |
x |
A vector of regressor |
z |
A data matrix of control variables |
q |
A vector of variable affecting threshold |
r01 |
Lower bounder of parameter space for r0 |
r02 |
Upper bounder of parameter space for r0 |
r11 |
Lower bounder of parameter space for r1 |
r12 |
Upper bounder of parameter space for r1 |
stp1 |
Step used in grid search of r0 |
stp2 |
Step used in grid search of r1 |
Value
A list with the elements
bols |
The OLS estimates when a kink effect is ignored. |
bt |
The regression coefficients when a kink effect is included in the model. |
gammahat0 |
The estimated threshold of the constant one in threshold parameters. |
gammahat1 |
The estimated threshold of the slop in threshold parameters. |
sig |
The sum of squred errors of the kink model. |
Examples
sta <- proc.time()
##Simulated data
set.seed(12345)
n=200
x = rnorm(n)
q = rnorm(n)
rt = 0.2 - 0.5*q
z = rnorm(n)
x1 = cbind(neg.part(x-rt),pos.part(x-rt),z)
b0 =c(1,2,1)
y = b0[1]*x1[,1]+b0[2]*x1[,2]+b0[3]*x1[,3]+ rnorm(n)
# set grid search paramaters
r01 = 0
r02 = 2
stp1 = 0.1
r11 = -10
r12 = 5
stp2 = 0.1
# estimate the model with a state-dependent threshold
est1 <- rkt(y,x,z,q,r01,r02,r11,r12,stp1,stp2)
proc.time() - sta