stat.skew: Measure skewness from cumulative distribution data

In dtavern/grainsizeR: Extract And Analyze Grain Size Distributions

Description

Measure skewness from cumulative distribution data

Usage

stat.skew(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 scale
method	Arithmetic methods: "inm" = Inman (1952) difference between mean and median divided by sorting;"inmod" = Modified Inman (1952) to account for tails;"fw" = Folk and Ward (1957) combination of the above;"war" = Warren (1974) simplified Folk and Ward;"gor" = Gordon (1992) less weighting on tails in case of unreliable data;"qsk" = Quartile skewness to use only inter-quartile data points;"tra" = Trask (1932) same as qsk but with mm units. Geometric method: "fred" = Fredle Index. Ratio of mean to sorting. "all" Output results of all methods in one dataframe

Value

numeric or dataframe output according to the method chosen. NOTE: reverse skewness signage if using

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.