estimlight: Fit Probability Distribution - Reduced Version

View source: R/estimlight.R

estimlightR Documentation

Fit Probability Distribution - 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 is a simplified alternative to estim.

Usage

estimlight(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

estimlight 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,
elicitate for fitting probability distributions to multiple indicator observations and for list of model distributions included.
Function qdev calculates sum of squares between the parameters of the indicator observation and model distributions.

Examples

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