DistributionPlotBinomial: Distribution Plot

In polySegratioMM: Bayesian mixture models for marker dosage in autopolyploids

Description

Plots probability density function given the parameters. May be useful when investigating parameter choice for prior distributions.

Usage

DistributionPlotBinomial(size = 200, prob = 0.5,
xlab = "Number of Successes", ylab = "Probability Mass", signif.digits = 3,
main = paste("Binomial Distribution: n =", size, "p =",
signif(prob, digits = signif.digits)))

DistributionPlotGamma(shape = 1, rate = 1, length = 100, xlab = "x",
ylab = "Density", main = bquote(paste("Gamma Distribution: ", alpha,
"=", .(signif(shape, digits = signif.digits)), ",", beta, "=",
.(signif(rate, digits = signif.digits)))), signif.digits = 3)

DistributionPlotNorm(mean = 0, sd = 1, length = 100, xlab = "x", ylab =
"Density", main = bquote(paste("Normal Distribution: ", mu, "=",
.(signif(mean, digits = signif.digits)), ",", sigma, "=", .(signif(sd,
digits = signif.digits)))), signif.digits = 3)

Arguments

size	number of trials (Binomial)
prob	probability of success (Binomial)
shape	shape parameter. Must be strictly positive. (Gamma)
rate	an alternative way to specify the scale (Gamma)
mean	mean (Normal)
sd	standard deviation (Normal)
xlab	x-axis label
ylab	y-axis label
signif.digits	number of significant digits for default main title
main	title for plot
length	Number of points to use for obtaining a smooth curve

Details

Based on functions in package Rcmdr

Value

None.

Author(s)

Peter Baker [e-mail]

See Also

Rcmdr Binomial Normal GammaDist

Examples

## Binomial distribution
DistributionPlotBinomial()
DistributionPlotBinomial(size=20, prob=0.2)

## Gamma distribution
DistributionPlotGamma()

## Normal distribution
DistributionPlotNorm()

polySegratioMM documentation built on May 2, 2019, 4:41 p.m.