fitdistrquantiles: Parameters of beta, normal or gamma distribution based on...

In HelpersMG: Tools for Environmental Analyses, Ecotoxicology and Various R Functions

Parameters of beta, normal or gamma distribution based on quantiles.

Description

Return the parameters of beta or gamm that fits the best the quantiles. The vector of probabilities can be obtained from names of quantiles.

Usage

fitdistrquantiles(
  quantiles = stop("At least two quantiles must be provided"),
  probs = NULL,
  scaled = FALSE,
  distribution = "beta"
)

Arguments

quantiles	Vector of quantiles.
probs	Numeric vector of probabilities with values in [0,1].
scaled	Used scaled least-square.
distribution	Distribution to be fitted: beta, normal, or gamma.

Details

fitdistrquantiles returns the parameters of beta, normal or gamma distribution

Value

Parameters of beta, normal or gamma distribution based on quantiles.

Author(s)

Marc Girondot [e-mail]

Examples

rd <- rbeta(100000, shape1 = 0.7, shape2 = 6.2, ncp=0)
(q <- quantile(rd, probs=c(0.025, 0.5, 0.975)))

(best <- fitdistrquantiles(quantiles = q, probs = c(0.025, 0.5, 0.975), 
                           scaled=FALSE, distribution = "beta"))
rd10000 <- rbeta(10000, shape1 = best["shape1"], shape2 = best["shape2"], ncp=best["ncp"])
quantile(rd10000, probs=c(0.025, 0.5, 0.975))

# Here the probabilities are obtained from names of quantiles
(best <- fitdistrquantiles(quantiles = q, scaled=FALSE, distribution = "beta"))
rd10000 <- rbeta(10000, shape1 = best["shape1"], shape2 = best["shape2"], ncp=best["ncp"])
quantile(rd10000, probs=c(0.025, 0.5, 0.975))

# If only two quantiles are provided, ncp cannot be fitted
(q2 <- quantile(rd, probs=c(0.025, 0.975)))
(best <- fitdistrquantiles(quantiles = q2, scaled=FALSE, distribution = "beta"))
rd10000 <- rbeta(10000, shape1 = best["shape1"], shape2 = best["shape2"])
quantile(rd10000, probs=c(0.025, 0.975))
x <- seq(from=0.00, to=1, by=0.001)
plot(x=x, y=pbeta(x, shape1 = best["shape1"], shape2 = best["shape2"]), 
     las=1, bty="n", type="l", ylim=c(0, 1))
segments(x0=q2[1], x1=q2[1], y0=0, y1=1, lty=2)
segments(x0=q2[2], x1=q2[2], y0=0, y1=1, lty=2)

(best <- fitdistrquantiles(quantiles = q, probs = c(0.025, 0.5, 0.975), 
                           scaled=FALSE, distribution = "gamma"))
rd10000 <- rgamma(10000, shape = best["shape"], scale = best["scale"])
quantile(rd10000, probs=c(0.025, 0.5, 0.975))

(best <- fitdistrquantiles(quantiles = c(10, 20, 30), probs = c(0.025, 0.5, 0.975), 
                           scaled=FALSE, distribution = "normal"))
rd10000 <- rnorm(10000, mean = best["mean"], sd = best["sd"])
quantile(rd10000, probs=c(0.025, 0.5, 0.975))

HelpersMG documentation built on Oct. 5, 2023, 5:08 p.m.