In irenerwang/binomial:

knitr::opts_chunk$set(collapse = T, comment = "#>")
library(binomial)

Binomial

The package "binomial" is a minimal implementation for simulating binomial distributions and random variables, and to visualize the relative probabilities of successes in such binomial variable with those

Calculations

The binomial package contains methods "bin_mean", "bin_variance", "bin_mode", "bin_skewness", and "bin_kurtosis. All these methods take in a double for the trials and another double for the probability of success as inputs. They use those inputs to calculate those statistics and returns another double.

We can also use the "bin_choose" and "bin_probability" methods to calculate the number of combinations possible with your inputted total trials and number of successes, and the probability of getting a certain number of successes. "bin_choose" takes in two doubles, the first is the total number of trials and the second is the number of successes. "bin_probability" takes in three doubles, the first is the number of successes, the second is the number of trials, and the third is the probability of success.

bin_mean(10,0.3)
bin_variance(10,0.3)
bin_mode(10,0.3)
bin_skewness(10,0.3)
bin_kurtosis(10,0.3)

bin_choose(10, 3)
bin_probability(3, 10, 0.3)

Creating Distributions, Cumulative Densities, and Random Variables

We can create binomial distributions by using the "bin_distribution" method. It takes in the number of trials and the probability of success, and returns a "bindis" object. You can see what the "plot.bindis" function, which gives a barplot of the probabilities of getting that many successes.

this_bin <- bin_distribution(10, 0.3)
this_bin
plot.bindis(this_bin)

We can create cumulative binomial distributions by using the "bin_cumulative" method. It takes in the number of trials and the probability of success, and returns a "bincum" object. You can see what the "plot.bincum" function, which gives a line plot of the probabilities of getting that many successes.

this_cum <- bin_cumulative(10, 0.3)
this_cum
plot.bincum(this_cum)

The function "bin_variable" creates a binomial random variable. It takes in two paramters, the number of trials and the probability of success. It returns a "binvar" object. We can look at the parameters of the "binvar" object by passing it into the "print.binvar" method. We can get its summary with all of the parameters and measurements by passing the "binvar" object into the "summary.binvar" method, and we can view them with the "print.summary.binvar" method.

current_bin <- bin_variable(10, 0.5)
current_bin
print.binvar(current_bin)

print.summary.binvar(current_bin)

irenerwang/binomial documentation built on May 3, 2019, 1:29 p.m.