sim_lod: Simulate limit of detection data

In Columbia-PRIME/pcpr: Principal Component Pursuit for Environmental Epidemiology

Simulate limit of detection data

Description

sim_lod() simulates putting the columns of a given matrix D under a limit of detection (LOD) by calculating the given quantile q of each column and corrupting all values < the quantile to NA, returning the newly corrupted matrix, the binary corruption mask, and a vector of column LODs.

Usage

sim_lod(D, q)

Arguments

D	The input data matrix.
q	A double in the range ⁠[0, 1]⁠ specifying the quantile to use in creating the column-wise LODs. Passed as the probs argument to the quantile() function.

Value

A list containing:

• D_tilde: The original matrix D corrupted with < LOD NA values.

• tilde_mask: A binary matrix of dim(D) specifying the locations of corrupted entries (1) and uncorrupted entries (0).

• lod: A vector with length(lod) == ncol(D) providing the simulated LOD values corresponding to each column in the D_tilde.

See Also

sim_na(), impute_matrix(), sim_data()

Examples

D <- sim_data(5, 5, sigma = 0.8)$D
D
sim_lod(D, q = 0.2)

Columbia-PRIME/pcpr documentation built on April 14, 2025, 8:33 a.m.