mean_detrended.dm: Calculate the mean detrended dendrometer series

In dendRoAnalyst: A Tool for Processing and Analyzing Dendrometer Data

Calculate the mean detrended dendrometer series

Description

Computes a mean detrended dendrometer series across multiple trees from the output of dm.detrend.fit().

This is useful for creating one representative detrended series for a species, site, or treatment group after detrending individual dendrometer series.

Optionally, the function can:

• calculate a robust mean using a trimmed mean across trees,

• remove temporal autocorrelation from the mean detrended series using forecast::auto.arima(),

• rescale the autocorrelation-removed series so it stays non-negative and has mean = 1 within each vegetation season.

Usage

mean_detrended.dm(
  detrended_dm,
  series = NULL,
  ac1.remove = TRUE,
  robust.mean = TRUE,
  trim = 0.15,
  seasonal_rescale = TRUE
)

Arguments

detrended_dm	An object of class "dm_detrended" returned by dm.detrend.fit(), or a data frame in the same wide format as $detrended_data.
series	Optional character vector of tree/series names to include. Default is NULL, meaning all available detrended series are used.
ac1.remove	Logical. If TRUE, removes temporal autocorrelation from the mean detrended series using forecast::auto.arima() applied separately within each season. Default is TRUE.
robust.mean	Logical. If TRUE, calculates a trimmed mean across trees at each time step. Default is TRUE.
trim	Proportion to trim from each tail when robust.mean = TRUE. Default is 0.15.
seasonal_rescale	Logical. If TRUE, the autocorrelation-removed series is shifted to non-negative values and rescaled to mean = 1 within each season. Default is TRUE.

Value

A tibble of class "mean_dm_detrended" containing:

• metadata columns copied from the detrended input,

• STD_DDM: the mean detrended series,

• RES_DDM: the autocorrelation-removed mean detrended series (returned only when ac1.remove = TRUE).

Examples

fit1 <- dm.growth.fit(
  df = gf_nepa17,
  TreeNum = 1:2,
  method = "gompertz",
  year_mode = "yearly",
  verbose = FALSE
)

det1 <- dm.detrend.fit(fit1)

m_det <- mean_detrended.dm(det1)
head(m_det, 10)

dendRoAnalyst documentation built on May 20, 2026, 5:07 p.m.