estimlight.fct: Fit Probability Distribution to one Indicator Observation,...

In NINAnor/NIcalc: Functions to Calculate a Nature Index

Fit Probability Distribution to one Indicator Observation, reduced Version

Description

Function that, in the continuous case, fits a lognormal distribution to an expected value and two quantiles, or fits a Poisson- or negative binomial distribution in the discrete case, using the least square criterion. estimlight.fct is a simplified alternative to estim.fct.

Usage

estimlight.fct(obsval = NULL, proba = c(0.25, 0.75), type = "continuous")

Arguments

obsval	double, length = 3, observed mean and quantiles in the sequence c(lower.quantile, mean, upper.quantile)
proba	double, length = 2, quantiles supplied in "obsval". Default is the lower and upper quartiles
type	character, length = 1, type of measurement scales. Valid types are "continuous" and "discrete". When type = "continuous", a continuous model is fitted to the indicator observation. When type = "discrete", a discrete model is fitted.

Value

estim.fct returns a data.frame with dim = c(1,4), consisting of the following vectors
[[1]] $distrib character, selected family for model distribution, i.e. one of c("LogNormal", "NegBinom", "Poisson").
[[2]] $mu double, first parameter of fitted model distribution
[[3]] $sig double, second parameter of fitted model distribution
[[4]] $crit double, sum of squared deviations between observed parameters and those of the fitted model distribution.

Author(s)

Nigel Yoccoz and Bård Pedersen

See Also

estim.fct,
elicitate for fitting probability distributions to multiple indicator observations and for list of model distributions included,
qdev for calculating sum of squares between obsval and model.

Examples

estimlight.fct(obsval = c(6,13,25))
estimlight.fct(obsval = c(6,13,25),proba = c(0.025,0.975), type = "continuous")
estimlight.fct(obsval = c(6,13,25),proba = c(0.025,0.975), type = "discrete")

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