MECfda_simDataGen_ME: Simulation Data Generation: Measurement Error Bias Correction...

In MECfda: Scalar-on-Function Regression with Measurement Error Correction

Simulation Data Generation: Measurement Error Bias Correction of Scalar-on-function Regression

Description

Generate data set for measurement error bias correction methods for scalar-on-function regression in package MECfda

Usage

MECfda_simDataGen_ME(
  N = 100,
  J_W = 7,
  forwhich = c("MEM", "IV", "CLS", "IV.SIMEX"),
  t_interval = c(0, 1),
  n_t = 24,
  seed = 0
)

Arguments

N	Sample size.
J_W	Number of repeated measurement (period), if applicable.
forwhich	For which method of measurement error bias correction method the data set is generated. There are two options: 'MEM','IV','CLS','IV.SIMEX'.
t_interval	A 2-element vector, represents an interval, means the domain of the functional covariate. Default is c(0,1), represent interval [0,1].
n_t	Number of measurement time points.
seed	Pseudo-random number generation seed.

Value

return a list that possibly contains following elements.

Y	An atomic vector of response variable
Z	A dataframe with a binary and a continuous scalar-valued covariate.
W	Observed values of function-valued covariate.
M	Instrumental vairable.
t_interval	Same as in the input argument.
t_points	Sequence of the measurement (time) points.

Examples

for (i in 1:4) {MECfda_simDataGen_ME(forwhich = c('MEM','IV','CLS','IV.SIMEX')[i])}

MECfda documentation built on April 3, 2025, 10:07 p.m.