ewma: Exponentially Weighted Moving Average (EWMA)

In growthcleanr: Data Cleaner for Anthropometric Measurements

Exponentially Weighted Moving Average (EWMA)

Description

ewma calculates the exponentially weighted moving average (EWMA) for a set of numeric observations over time.

Usage

ewma(agedays, z, ewma.exp, ewma.adjacent = TRUE)

Arguments

agedays	Vector of age in days for each z score (potentially transformed to adjust weighting).
z	Input vector of numeric z-score data.
ewma.exp	Exponent to use for weighting.
ewma.adjacent	Specify whether EWMA values excluding adjacent measurements should be calculated. Defaults to TRUE.

Value

Data frame with 3 variables:

• The first variable (ewma.all) contains the EWMA at observation time excluding only the actual observation for that time point.

• The second variable (ewma.before) contains the EWMA for each observation excluding both the actual observation and the immediate prior observation.

• The third variable (ewma.after) contains the EWMA for each observation excluding both the actual observation and the subsequent observation.

Examples

# Run on 1 subject, 1 type of parameter
df_stats <- as.data.frame(syngrowth)
df_stats <- df_stats[df_stats$subjid == df_stats$subjid[1] &
                       df_stats$param == "HEIGHTCM", ]

# Get the uncentered z-scores
measurement_to_z <- read_anthro(cdc.only = TRUE)
sd <- measurement_to_z(df_stats$param,
                       df_stats$agedays,
                       df_stats$sex,
                       df_stats$measurement,
                       TRUE)

# Calculate exponentially weighted moving average
e_df <- ewma(df_stats$agedays, sd, ewma.exp = -1.5)

growthcleanr documentation built on June 24, 2024, 5:16 p.m.