Myerson: Density function for Generalized Lognormal distribution (aka...

In dmi3kno/qpd: Tools for Quantile-Parametrized Distribiutions

Density function for Generalized Lognormal distribution (aka probit Myerson).

Description

Density function for Generalized Lognormal distribution (aka probit Myerson).

Usage

qMyerson(p, q1, q2, q3, alpha = 0.25, lower.tail = TRUE, log.p = FALSE)

fMyerson(
  p,
  q1,
  q2,
  q3,
  alpha = 0.25,
  log = FALSE,
  lower.tail = TRUE,
  log.p = FALSE
)

dqMyerson(
  p,
  q1,
  q2,
  q3,
  alpha = 0.25,
  log = FALSE,
  lower.tail = TRUE,
  log.p = FALSE
)

rMyerson(n, q1, q2, q3, alpha = 0.25)

dMyerson(x, q1, q2, q3, alpha = 0.25, log = FALSE)

pMyerson(q, q1, q2, q3, alpha = 0.25, lower.tail = TRUE, log.p = FALSE)

Arguments

p	vector of probabilities
q1, q2, q3	numeric values representing bottom quantile, middle quantile (50th percentile) and top quantile. Quantiles are assumed to be symmetrical.
alpha	numerical fixed proportion of distribution below the bottom quantile. Default value is 0.25
lower.tail	logical; if TRUE (default), probabilities are P[X\leq x], otherwise, P[X > x]
log, log.p	logical; if TRUE, probabilities p are given as log(p)
n	number of observations. If 'length(n)>1“, the length is taken to be the number required.
x, q	vector of quantiles.

Value

a vector of probabilities of length equal to length(x)

a vector of exceedance probabilities of length equal to length(x).

Examples

qMyerson(0.25, 10, 20, 40)
fMyerson(0.25, 10, 20, 40)
fMyerson(0.25, 10, 20, 40)
rMyerson(1, 10, 20, 40)
dMyerson(15, 10, 20, 40)
pMyerson(0.25, 10, 20, 40)

dmi3kno/qpd documentation built on Sept. 29, 2024, 6:39 p.m.