Function that generates and displays m repeated samples of n
Bernoulli trials with a given probability of success.
Usage
bino.gen(samples, n, pi)
Arguments
samples
number of repeated samples to generate
n
number of Bernoulli trials
pi
probability of success for Bernoulli trial
Value
simulated.distribution
Simulated binomial distribution
theoretical.distribution
Theoretical binomial distribution
Author(s)
Alan T. Arnholt
Examples
bino.gen(1000, 20, 0.75)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(PASWR)
Loading required package: e1071
Loading required package: MASS
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/PASWR/bino.gen.Rd_%03d_medium.png", width=480, height=480)
> ### Name: bino.gen
> ### Title: Simulating Binomial Distribution
> ### Aliases: bino.gen
> ### Keywords: distribution
>
> ### ** Examples
>
> bino.gen(1000, 20, 0.75)
$simulated.distribution
Successes
0 1 2 3 4 5 6 7 8 9 10 11 12
0.001 0.018 0.071 0.146 0.212 0.174 0.172 0.103 0.066 0.023 0.012 0.001 0.001
$theoretical.distribution
0 1 2 3 4 5 6 7 8 9 10 11 12
0.003 0.021 0.067 0.134 0.190 0.202 0.169 0.112 0.061 0.027 0.010 0.003 0.001
13 14 15 16 17 18 19 20
0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.