stat.mean: Compute mean grain size from cumulative size distribution

In dtavern/grainsizeR: Extract And Analyze Grain Size Distributions

Description

Compute mean grain size from cumulative size distribution

Usage

stat.mean(sieve_size, cumu, units = "phi", method = "all")

Arguments

sieve_size	vector of sieve sizes related to input cumulative distribution
cumu	cumulative distribution pertaining to sieve sizes
units	sieve size units "phi" = phi scale, "mm" = milimeter (metric) scale
method	Algebraic: "inm" = Inman (1952) very simple calculation focus on central data;"tra" = Trask (1932) use interquartile values;"fw" = Folk and Ward (1957) incorporate median value to Inman equation;"brig" = Briggs (1977) use all percentile values (10, 20, 30...80, 90) to incorprate distribution;"mccam" = McCammon (1962) Similar to Briggs but on the 5th percentiles. Geometric: "sqrt" = Geometric approach similar to Inman but with metric log-normal distributions;"cubr" = Similar to square root but incorporate D50;"log" = Log transform metric data to calculate and backtransform result to original units (works for log-normal distributions); "all" = All outputs into a dataframe

Value

dataframe or value containing specified measures of mean

Source

see Bunte and Abt (2001) for examples and equations. Bunte, Kristin, and Steven R. Abt. "Sampling surface and subsurface particle-size distributions in wadable gravel-and cobble-bed streams for analyses in sediment transport, hydraulics, and streambed monitoring." (2001).

dtavern/grainsizeR documentation built on May 15, 2019, 4:53 p.m.