README.md

In kyung541/binomial: Calculate Probabilities of a Binomial Random Variable

This is a package name "binomial" that careate by a student in University of Californai, Berkeley. Please be aware that this function is not yet perfect. Use it at your own risk

binomial

Overview

"binomial" is a minimal R package that provides functions to calculate a random binomial variable.

• bin_choose() creates a random binomial variable object (of class "numeric")

• bin_probability() calculate the probability of the chosen variable, producing a "numeic" object.

• bin_distribution() create a data frame that display the distribution of the chosen variable (of class "bindis" and "data.frame")

• plot() method for a "bindis" object to plot frequencies of probability of success.

• "bin_cumulative()" create a data frame which display the cumulative probability as well as the distribution as well ( of class "bincum" and "data.frame")

• plot() method for a "bincum" object to plot the frequecies of the cumulative of success.

• "bin_variable()" calcuate different satistical information for the choosen objects (of class binvar), eg., mean, mode,variance, skewness **and** kurtosis. To do show, there are private function such as "aux_mean()", "aux_variable()" and "aux_mode()" etc that will help us calculate using the imformation you input.

• summary() method for a "binvar" object ( create into object of class "summary.binvar")

• print() method for a "summary.binvar" object to display in a user-freindly way

Motivation

This package has been developed to help user to get all the infomation they need for binomial variable in a very fast and easy way.

Installation

Install the development version from GitHub via the package "devtools":

# development version from GitHub:
install.packages("devtools") 
# install "cointoss"
devtools::install_github("ucb-stat133/cointoss")

Usage

library(binomial)
# default random binomial variable where n = trials and k = success
variable <- bin_choose( n = 5, k = 2)
variable 
#>10

# Calculate the probaility 
binpro = bin_probability(success = 2, trials=5, prob=0.5)
binpro
#> 0.315

# Calculating the binomial distribution
bindist = bin_distribution(trials = 5, prob = 0.5)
bindist

# plot the binomial distribution
bindistrP = plot(bindist)
bindistrP

#  Calculating the binomial cumulative distributioon 
bincumu = bin_cumulative(trials = 5, prob = 0.5)
bincumu

# Plot the binomial cumulative dirtribution
bincumuP = plot(bincumu)
bincumuP

# Listing the variables 
binvar = bin_variable(trials = 10, prob = 0.3)
binvar

# Summary of the variables
binvarsum = summary(binvar)
binvarsum

kyung541/binomial documentation built on May 5, 2019, 12:27 a.m.