dshift: Compute density function of a shifted distribution

In veronicagiro/qshift: Distribution factory

Description

Compute density function of a shifted distribution

Usage

dshift(dist)

Arguments

dist

character string indicating the distribution name. It can be set as: beta Beta Distribution binom Binomial Distribution cauchy Cauchy Distribution chisq Chi-Square Distribution exp Exponential Distribution f F Distribution gamma Gamma Distribution geom Geometric Distribution hyper Hypergeometric Distribution logis Logistic Distribution lnorm Log Normal Distribution nbinom Negative Binomial Distribution norm Normal Distribution pois Poisson Distribution t Student t Distribution unif Uniform Distribution weibull Weibull Distribution wilcox Wilcoxon Rank Sum Statistic Distribution signrank Wilcoxon Signed Rank Statistic Distribution

Value

numeric vector of the density function of a specified distribution

Examples

# Binomial distribution
db <- dshift("binom")
zero_shift <- db(x = c(1,2,3,4,5), size = 6, prob = 0.5, shift = 0)
zero_shift
one_shift <- db(x = c(1,2,3,4,5), size = 6, prob = 0.5, shift = 1)
one_shift
two_shift <- db(x = c(1,2,3,4,5), size = 6, prob = 0.5, shift = 2)
two_shift

# Normal Distribution
dn <- dshift("norm")
zero_shift <- dn(x = c(1,2,3,4,5), mean = 2, sd = 1, shift = 0)
zero_shift
one_shift <- dn(x = c(1,2,3,4,5), mean = 2, sd = 1, shift = 1)
one_shift
two_shift <- dn(x = c(1,2,3,4,5), mean = 2, sd = 1, shift = 2)
two_shift

veronicagiro/qshift documentation built on May 3, 2019, 6:10 p.m.