MEM_X_hat {MECfda} | R Documentation |
Get MEM substitution for (generalized) linear regression with one functional covariate with measurement error.
Description
The function to get the data of \hat X_i(t)
using the mixed model based
measurement error bias correction method
proposed by Luan et al.
See ME.fcRegression_MEM
Usage
MEM_X_hat(
data.W,
method = c("UP_MEM", "MP_MEM", "average"),
d = 3,
family.W = c("gaussian", "poisson"),
smooth = FALSE
)
Arguments
data.W |
A 3-dimensional array, represents |
method |
The method to construct the substitution |
d |
The number of time points involved for MP_MEM (default and miniumn is 3). |
family.W |
Distribution of |
smooth |
Whether to smooth the substitution of |
Value
A numeric value matrix of \hat X_i(t)
.
References
Luan, Yuanyuan, et al. "Scalable regression calibration approaches to correcting measurement error in multi-level generalized functional linear regression models with heteroscedastic measurement errors." arXiv preprint arXiv:2305.12624 (2023).
Examples
data(MECfda.data.sim.0.1)
X_hat = MEM_X_hat(data.W = MECfda.data.sim.0.1$W,
method = 'UP_MEM',
family.W = "gaussian")