dm_wavelet: Wavelet analysis of dendrometer series
In dendRoAnalyst: A Tool for Processing and Analyzing Dendrometer Data

View source: R/dm_wavelet.R

dm_wavelet

R Documentation

Wavelet analysis of dendrometer series

Description

Performs continuous wavelet analysis on dendrometer time series.

The function can work with:

raw dendrometer series from a data frame,
detrended dendrometer series from dm.detrend.fit() output,
first differences of either raw or detrended series.

It automatically:

identifies the temporal resolution of the input series,
regularizes the series to a complete time grid,
optionally interpolates missing values,
performs wavelet analysis separately for each selected tree/series,
converts wavelet periods to hours for summary and plotting.

Usage

dm_wavelet(
  x,
  TreeNum = "all",
  source = c("auto", "raw", "detrended", "first_diff"),
  detrended_col = c("detrended_data"),
  na_action = c("interpolate", "fail"),
  loess_span = 0.75,
  dj = 1/20,
  lowerPeriod = NULL,
  upperPeriod = NULL,
  make_pval = TRUE,
  n_sim = 10,
  verbose = TRUE
)

Arguments

`x`	Input data. Either: data.frame First column must be time, remaining selected numeric columns are dendrometer series. dm_detrended object Uses `x$detrended_data` as input.
`TreeNum`	Either `"all"` to use all available dendrometer series, a numeric vector selecting series by position, or a character vector of series names.
`source`	Which series to analyze. One of: '"auto"' Uses raw series for a data frame input and detrended series for a `dm_detrended` object. '"raw"' Use raw dendrometer series from a data frame input. '"detrended"' Use detrended series from a `dm_detrended` object. '"first_diff"' Use first differences of the available input series.
`detrended_col`	For `dm_detrended` input, which table to use: `"detrended_data"`.
`na_action`	How to handle missing values after completing the regular time grid. One of: '"interpolate"' Linearly interpolate internal gaps and carry ends forward/backward. '"fail"' Stop if missing values are found.
`loess_span`	Smoothing span passed to `WaveletComp::analyze.wavelet()`.
`dj`	Frequency resolution parameter passed to `WaveletComp::analyze.wavelet()`.
`lowerPeriod`	Optional lower period bound in native time units of the detected input resolution. If `NULL`, the default from `WaveletComp::analyze.wavelet()` is used.
`upperPeriod`	Optional upper period bound in native time units of the detected input resolution. If `NULL`, the default from `WaveletComp::analyze.wavelet()` is used.
`make_pval`	Logical; if `TRUE`, compute Monte Carlo significance.
`n_sim`	Number of simulations used when `make_pval = TRUE`.
`verbose`	Logical; if `TRUE`, prints a completion message.

Value

An object of class "dm_wavelet" with elements:

call: The matched function call.
input_type: Either "raw" or "dm_detrended".
source: Series source actually used.
series: Character vector of analyzed series names.
time_unit: Detected time unit of the input series.
dt: Detected time step in native units.
dt_hours: Detected time step expressed in hours.
resolution_seconds: Detected time step in seconds.
data_used: Regularized time series used for analysis.
results: Named list of wavelet results, one per series. Each entry contains the original WaveletComp object plus time and period-in-hours information.
settings: Analysis settings.