sim_gait_data

A synthetic longitudinal dataset representing daily step counts of an older adult.
Used to demonstrate the "Vanishing Variance" problem.

datasets

Provides functions for data normalization and transformation in
preprocessing stages. Implements scaling methods (min-max, Z-score, L2
normalization) and power transformations (Box-Cox, Yeo-Johnson). Box-Cox
transformation is described in Box and Cox (1964)
<doi:10.1111/j.2517-6161.1964.tb00553.x>, Yeo-Johnson transformation in
Yeo and Johnson (2000) <doi:10.1093/biomet/87.4.954>.

Rui Gong

prepkit

Data Normalization and Transformation

sim_gait_data function

A data frame with 200 rows and 2 variables:<dl>
 <dt>day</dt>
<dd>Integer. Time index (Days 1-200).</dd> <dt>steps</dt>
<dd>Numeric. Daily step count with habitual plateau and anomalies.</dd>
</dl>

Format

Simulated Geriatric Gait Data — sim_gait_data

A data frame with 200 rows and 2 variables:<dl>
 <dt>day</dt>
<dd>Integer. Time index (Days 1-200).</dd>

 <dt>steps</dt>
<dd>Numeric. Daily step count with habitual plateau and anomalies.</dd>


</dl>

sim_gait_data: Simulated Geriatric Gait Data

Description

Usage

Arguments

Format