get.n: Calculate the number of grains required to achieve a desired...

In provenance: Statistical Toolbox for Sedimentary Provenance Analysis

Calculate the number of grains required to achieve a desired level of sampling resolution

Description

Returns the number of grains that need to be analysed to decrease the likelihood of missing any fraction greater than a given size below a given level.

Usage

get.n(p = 0.05, f = 0.05)

Arguments

p	the probability that all n grains in the sample have missed at least one fraction of size f
f	the size of the smallest resolvable fraction (0<f<1)
n	the number of grains in the sample

Value

the number of grains needed to reduce the chance of missing at least one fraction f of the total population to less than p

References

Vermeesch, Pieter. "How many grains are needed for a provenance study?." Earth and Planetary Science Letters 224.3 (2004): 441-451.

Examples

# number of grains required to be 99% that no fraction greater than 5% was missed:
print(get.n(0.01))
# number of grains required to be 90% that no fraction greater than 10% was missed:
print(get.n(p=0.1,f=0.1))

provenance documentation built on May 29, 2024, 4:23 a.m.