branch_volume_weighted_stats: Calculate volume weighted branch statistics

In tReeTraits: Calculate Tree Traits from Terrestrial Lidar

Calculate volume weighted branch statistics

Description

This function calculates statistics on branch diameters weighted by the volume of branches of that size based on outputs from 'branch_size_distribution()'. The user defined function 'FUN' can take any form of f(x) where x is a vector of diameters of length 1 for every mL of volume of that branch size class. See Details for recommended values for 'FUN'. #Details Values of central tendency are recommended, but not variance since the weighted means are simulated.

Usage

branch_volume_weighted_stats(qsm, breaks = NULL, FUN = function(x) mean(x))

Arguments

qsm	a QSM loaded using '[load_qsm()]'.
breaks	numeric – a vector of diameter classes (in cm) by which to summarize branch volume. If 'NULL' the branch of branch sizes will be distributed across 1 cm bins.
FUN	function – central tendency function to be weighted based on branch volume.

Details

Recommended values of 'FUN' are:

Mean FUN = function(x) mean(x)

Median FUN = function(x) median(x)

Skewness FUN = function(x) 3*(mean(x) - median(x)) / sd(x)

Value

A numeric value representing the volume-weighted statistic calculated by 'FUN' across branch diameter classes.

Examples

qsm_file = system.file("extdata", "tree_0744_qsm.txt", package='tReeTraits')
qsm = load_qsm(qsm_file)
branch_distribution = branch_size_distribution(qsm, plot=TRUE)
print(branch_distribution)

#volume-weighted mean
branch_volume_weighted_stats(qsm, FUN = function(x) mean(x))

#volume-weighted median
branch_volume_weighted_stats(qsm, FUN = function(x) median(x))

# volume-weighted skewness
branch_volume_weighted_stats(qsm, FUN = function(x) 3*(mean(x) - median(x)) / sd(x))

tReeTraits documentation built on Feb. 26, 2026, 1:07 a.m.