In TylerPardun/MATH4753pard0003: Lab4 Package

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title: "Tyler Pardun - Lab Functions" author: "Tyler Pardun" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Tyler Pardun - Lab Functions} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} %\VignetteEngine{rmarkdown::render}

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(MATH4753pard0003)

Introduction

In this package, 5 functions are defined from previous labs and examples are shown below.

Mymult Function

MATH4753pard0003::mymult(iter=100,n=10, p=c(1,1,1,1)/4)

This function inputs a vector of an arbitrary number of categories with a specified number of iterations and a size n. This function will graph the relative frequencies of n random samples and creates a histogram out of it.

Myncurve Function

MATH4753pard0003::myncurve(a=10, mu=3, sigma=1)

This function will input an arbitrary number with a specified mean and standard deviation. The output will be a normal distribution with the probability of x is less than or equal to that specifed number.

Myplot Function

MATH4753pard0003::myquadratic(x=100)

This function take an input X value and will return the yhat value from the equation specified in Lab 4.

Mycltp Function

MATH4753pard0003::mycltp(n=20,iter=10000,lambda=10)

This function takes a sample size of n, an abirtrary number of iterations and a specifed lambda value for a Poisson distribution. The output consits of a histogram of the density of the discrete values, a barplot of the sampled y values and a probability function of all possible y values.

Myboot2 Function

set.seed(68)
sam=rnorm(20,mean=10,sd=4)
MATH4753pard0003::myboot2(iter=10000,x=sam,fun="mean",alpha=0.05)

This function takes a specified distriubtion and will perform a bootstrap sample to it to obtain the lower and upper bounds of a specified confidence interval.

Myci Function

MATH4753pard0003::myci(x=rnorm(30,mean=10,sd=3))

This function takes a specified distriubtion and will compute the lower and upper bounds of a the 95% confidence interval.

Mymlnorm Function

y=c(10,12,13,15,12,11,10)
MATH4753pard0003::mymlnorm(y,color='black')

This function produces a 3 panel plot for the poisson distribution.

mybootpval Function

set.seed(55);x1=rnorm(30,mean=25, sd=5)
MATH4753pard0003::bootpval(x=x1,mu=22,test="two")

This function produces a histogram with accepted and rejected regions from a bootstrap resample from a given sample and a given null hypothesis about the mean of the sample.

TylerPardun/MATH4753pard0003 documentation built on Dec. 31, 2020, 5:34 p.m.