sim.chngpt: Simulation Function

In chngpt: Estimation and Hypothesis Testing for Threshold Regression

Simulation Function

Description

Generate simulation datasets for change point Monte Carlo studies.

Usage

sim.chngpt (mean.model = c("thresholded", "thresholdedItxn",
 "quadratic", "quadratic2b", "cubic2b", "exp",
 "flatHyperbolic", "z2", "z2hinge", "z2segmented",
 "z2linear", "logistic"), threshold.type = c("NA",
 "M01", "M02", "M03", "M10", "M20", "M30", "M11",
 "M21", "M12", "M22", "M22c", "M31", "M13", "M33c",
 "hinge", "segmented", "upperhinge", "segmented2",
 "step", "stegmented"), b.transition = Inf, family =
 c("binomial", "gaussian"), x.distr = c("norm",
 "norm3", "norm6", "imb", "lin", "mix", "gam",
 "zbinary", "gam1", "gam2", "fixnorm", "unif"), e. =
 NULL, mu.x = 4.7, sd.x = NULL, sd = 0.3, mu.z = 0,
 alpha = NULL, alpha.candidate = NULL, coef.z =
 log(1.4), beta = NULL, beta.itxn = NULL,
 logistic.slope = 15, n, seed, weighted = FALSE,
 heteroscedastic = FALSE, ar = FALSE, verbose = FALSE)

sim.twophase.ran.inte(threshold.type, n, seed)

sim.threephase(n, seed, gamma = 1, e = 3, beta_e = 5, f = 7, beta_f = 2, coef.z = 1)

Arguments

threshold.type	string. Types of threshold effect to simulate, only applicable when label does not start with sigmoid.
family	string. Glm family.
n
mu.z
seed
weighted
beta
coef.z	numeric. Coefficient for z.
beta.itxn	numeric. Coefficient for z.
alpha	numeric, intercept.
mu.x	numeric
sd.x	numeric
mean.model	numeric
x.distr	string. Possible values: norm (normal distribution), gam (gamma distribution). gam1 is a hack to allow e. be different
e.
verbose	Boolean
b.transition
sd
ar	autocorrelation
alpha.candidate	Candidate values of alpha, used in code to determine alpha values
e
beta_e
f
beta_f
logistic.slope
gamma
heteroscedastic	Boolean.

Details

mean.model, threshold.type and b.transition all affect mean models.

Value

A data frame with following columns:

y	0/1 outcome
x	observed covariate that we are interested in
x.star	unobserved covariate that underlies x
z	additional covariate

In addition, columns starting with 'w' are covariates that we also adjust in the model; columns starting with 'x' are covariates derived from x.

Examples

seed=2
par(mfrow=c(2,2))
dat=sim.chngpt(mean.model="thresholded", threshold.type="hinge", family="gaussian", beta=0, n=200, 
    seed=seed, alpha=-1, x.distr="norm", e.=4, heteroscedastic=FALSE)
plot(y~z, dat)
dat=sim.chngpt(mean.model="thresholded", threshold.type="hinge", family="gaussian", beta=0, n=200, 
    seed=seed, alpha=-1, x.distr="norm", e.=4, heteroscedastic=TRUE)
plot(y~z, dat)
dat=sim.chngpt(mean.model="z2", threshold.type="hinge", family="gaussian", beta=1, n=200, 
    seed=seed, alpha=1, x.distr="norm", e.=4, heteroscedastic=FALSE)
plot(y~z, dat)
dat=sim.chngpt(mean.model="z2", threshold.type="hinge", family="gaussian", beta=1, n=200, 
    seed=seed, alpha=1, x.distr="norm", e.=4, heteroscedastic=TRUE)
plot(y~z, dat)

chngpt documentation built on Feb. 16, 2023, 10:38 p.m.