makeDistribution: Create a distribution function to describe the uncertainty...

In NINAnor/NIcalc: Functions to Calculate a Nature Index

Create a distribution function to describe the uncertainty for an indicator

Description

This functions formats various representations of indicator uncertainty into a common structure for further processing

Usage

makeDistribution(input = NULL, distParams = NULL)

Arguments

input	Either "logNormal", "Poisson", a vector of values, or a data frame of possible values and value probabilities. See examples.
distParams	(optional) Parameters for the distribution function, if such is provided in 'input'. See examples.

Value

an object of class 'NIdistribution'

Author(s)

Jens Åström

See Also

sampleDistribution The vignette Distributions gives detailed descriptions of how to use makeDistribution to generate distribution objects when revising and updating the data set for an indicator.

Examples

myDist <- makeDistribution(input = "logNormal", distParams = list("mean" = 1, "sd" = 0.2))
sampleDistribution(myDist, 10)

myDist <- makeDistribution(input = "Poisson", distParams = list("lambda" = 3))
sampleDistribution(myDist, 10)

myProbs <- data.frame("est" = c(0.2, 0.23, 0.34, 0.4), "probs" = c(0.1, 0.4, 0.4, 0.1 ))
myDist <- makeDistribution(myProbs)
sampleDistribution(myDist, 10)

codaSamples <- rnorm(1000, mean = 0.87, sd = 0.3)
myDist <- makeDistribution(codaSamples)
sampleDistribution(myDist, 10)

NINAnor/NIcalc documentation built on Oct. 26, 2023, 9:37 a.m.