clt.plot: Diagnose the Central Limit Theorem

In adoocavo/Rstat_M1: Basic Statistical Methods in R

Diagnose the Central Limit Theorem

Description

Diagnose the Central Limit Theorem

Usage

clt.plot(dist, para, para2, ns = c(10, 30, 50), d = rep(0.5, 3),
  N = 10000, seed = 9857, sigknow = TRUE)

Arguments

dist	Name of population distribution ("exp","gamma","weibull","beta","norm", "t","chisq","f","pois","binom")
para	Parameter for the first population
para2	Parameter for the second population (if necessary)
ns	Sample size, Default: c(10, 30, 50)
d	Group width in histogram, Default: rep(0.5, 3)
N	Number of iterations, Default: 10000
seed	Seed value for generating random numbers, Default: 9857
sigknow	Logical value for known population variance, Default: TRUE

Examples

clt.plot("exp", para=5, d=rep(0.4, 3))
clt.plot("bin", para=0.1, ns=nv, d=c(1, 0.6, 0.5))

adoocavo/Rstat_M1 documentation built on March 19, 2022, 3:34 a.m.