kmean_infer: Inference method for the partially functional linear model.

In wangwustat/fdagroup: Latent Group Detection in Partially Functional Linear Regression Models

Description

This function outputs the standard error of the scarlar estimates and the confidence band of the functional coefficient.

Usage

kmean_infer(data_list, group, num_pca = 5, tau_1 = c(0.005, 0.05, 0.1),
  tau_2 = 0.1, boot_size = 5000)

Arguments

data_list	A list of data. Several elements must be present in the list. The reponse y, the functional covariate x_recv, the scalar covariates z, and an index matrix index. The functional covariate x_recv must be generated from the fda package by, e.g., spline smoothing. The scalar covariates z is a matrix. The index matrix index is a data.frame recording the structure of the data. The first column of index is the family number, the second column is the within family index. The column names of index must be ind_b and ind_w.
group	The estimated group membership from the function bic_kmean_est.
num_pca	The number of principal components.
tau_1	The confidence level is 1-tau_1, can be a vector.
tau_2	The proportion of the index of the functional coefficient that might be not covered by the band.
boot_size	The size of bootstrap sampling.

wangwustat/fdagroup documentation built on Dec. 5, 2019, 12:51 a.m.