drift_detect: Sensor drift detection

In dataprep: Fast, Efficient, and Versatile Data Preprocessing and Reshaping with 'C++', 'OpenMP' & 'SIMD'

Sensor drift detection

Description

Detects potential sensor drift by comparing rolling window statistics (mean or standard deviation) to their long-term baseline. Returns a logical matrix indicating time points where the rolling statistic deviates beyond a threshold.

Usage

drift_detect(data, cols = NULL, window = 30, threshold = 3,
             method = c("mean", "sd"), group = NULL,
             date_col = NULL, verbose = FALSE)

Arguments

data	A data frame, matrix, or numeric vector.
cols	Column indices or names of numeric variables. If NULL, all numeric columns are used.
window	Window size for rolling statistics.
threshold	Threshold in units of standard deviation. Values with absolute z-score above this are flagged as drift.
method	Rolling statistic to use: "mean" or "sd".
group	Optional grouping column for group-wise detection.
date_col	Optional time column (not required for calculation).
verbose	Logical; if TRUE, prints progress message.

Value

A logical matrix with rows corresponding to observations and columns to the selected variables. TRUE indicates suspected drift.

Examples

drift_detect(data[1:500, c(1, 4, 17:19)], cols = 3:5, window = 50, threshold = 3)

dataprep documentation built on Oct. 1, 2026, 5:07 p.m.