fdaPOIFD (version 2.0.0)

depthbasedreconstructionPOFD: Depth-based reconstruction of partially observed functional data

Description

This function implements the reconstruction procedure [1] which is based on the depth measure [2] for partially observed functional data. Missing trajectories are imputed by the mean of the k nearest neighbors within the envelope. The parameter k is tuned minimizing the Mean Squared Error of the reconstruction in the observed part of the curve.

Usage

depthbasedreconstructionPOFD(data, id_recons = 1:dim(data)[2])

Value

The reconstructed data matrix 'recons_data'.

Arguments

data

Data matrix `p` by `n`, being `n` the number of functions and `p` the number of grid points. The row names of the matrix should be the common evaluation grid and the column names the identifiers of each functional data.

id_recons

Vector indicating functions to be reconstructed. By default, all functions are reconstructed.

Details

[1] Elías, A., Jiménez, R., & Shang, H. L. (2023). Depth-based reconstruction method for incomplete functional data. Computational Statistics, 38(3), 1507-1535.

[2] Elías, A., Jiménez, R., Paganoni, A. M., & Sangalli, L. M. (2023). Integrated depths for partially observed functional data. Journal of Computational and Graphical Statistics, 32(2), 341-352.

Examples

data <- exampleData$PoFDintervals
recons_data <- depthbasedreconstructionPOFD(data, id_recons = 1:2)