generate_fake_data {simITS} | R Documentation |
Make fake data for testing purposes.
Description
Defaults have heavy seasonality, and an extra bump in impact kicks in at 12 months post-policy.
Usage
generate_fake_data(
t_min = -40,
t_max = 9,
t0 = 0,
rho = 0.5,
sd.omega = 1,
coef_line = c(20, 0.05),
coef_q = c(1, 0, -1, 0),
coef_temp = 0.1,
coef_sin = c(0, 0),
coef_tx = c(0, 0.25, 5)
)
Arguments
t_min |
Index of first month |
t_max |
Index of last month |
t0 |
Last pre-policy time point |
rho |
Autocorrelation |
sd.omega |
Standard deviation of the true residual |
coef_line |
Intercept and slope of the main trendline (list of 2). |
coef_q |
Coefficients for the four quarters (list of 4). |
coef_temp |
Coefficient for temperature. |
coef_sin |
Coefficents for sin and cos features (list of 2) |
coef_tx |
Coefficient for treatment post-policy (list of 3, initial offset, initial slope, additional slope past 12 months). Treatment is a piecewise linear function. |
Value
A data.frame
having month
, temperature
,
sin.m
, cos.m
, Q1
, Q2
, Q3
, Q4
,
post
, Ystr0
, Ystr
, Y
Examples
fdat = generate_fake_data(-100,100, rho = 0.95, coef_q=c(0,0,0,0), coef_temp = 0)
plot( fdat$month, fdat$Y, type="l" )
fdat2 = generate_fake_data(-100, 100, rho = 0.0, coef_q=c(0,0,0,0), coef_temp = 0)
plot( fdat$month, fdat2$Y, type="l" )
[Package simITS version 0.1.1 Index]