In austinragotzy/mathstat: Introduction to Mathematical Statistics R Package

knitr::opts_chunk$set(
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Overview

This package illustrates the applicability of the concepts and alogrithms covered in 8th edition of the text Introduction to Mathematical Statics by Hogg, McKean, and Craig (2018). The topics in which these functions apply to includes but are not limited to the following:

1. Probability and Distributions
2. Multivariate Distributions
3. Some Special Distributions
4. Some Elementary Statistical Inferences
5. Consistency and Limiting Distributions
6. Maximum Likelihood Methods
7. Sufficiency
8. Optimal Test of Hypothesis
9. Inference About Normal Linear Models
10. Nonparametric and Robust Statistics
11. Bayesian Statistics

Below consists of the list of function within the mathstat package.

Functions

--A--

abgame Coin Flip versus Die Roll Game
aresimcn A Relative Efficency Investigation Simulation

--B--

bday Birthday Solver
betaplts Beta Distribution Plots
binomci Binomial distribution Confidence Interval
binompower Power Functions for Binomial Tests
bootstrapcis64 Percentile Bootstrap Confidence Interval
boottestonemed Bootstrap Test One Median
boottesttwo Bootstrap Testing Procedure

--C--

chistable Chi-Square Distribution
cipi Confidence Interval and Predictive Interval for Linear Models
condsim1 Observation Generator

--D--

data AZT doses
dcn PDF of Contaminated Normal
dex165 Probability Mass Function for Exercise 1.6.5
dlogF Density of Log Distribution
dloggamma Density of Log Gamma Distribution

--E--

ellipmake Plot Ellipse
empalphacn Emperical Alpha
ex158 Piecewise CDF Graph
ex1427 Number Drawing Game

--F--

fp1 F-Distribution Table for Upper 0.05 Critical Points
fp2 F-Distribution Table for Upper 0.05 Critical Points
fp3 F-Distribution Table for Upper 0.01 Critical Points
fp4 F-Distribution Table for Upper 0.01 Critical Points
ftable F-Distribution Table for 0.05, 0.25, and 0.01 Critical Points

--G--

getcis Get Confidence Intervals
gibbser2 Gibbs Sampler
gibbser3 Gibbs Sampler with Bayesian Inference

--H--

hcplot Hair Color Plot
hierarch1 Hierarchal Bayes Model

--M--

mcpbon Bonferroni's Multiple Comparisons Procedure
mcpfisher Fisher's Protected Least Significance Difference
mixnormal The First Iteration of the EM Step
mlelogistic MLE Estimation of Location Based on a Logistic Distribution
mses Mean Squared Error
multitrial Multinomial Trial Simulation

--N--

newfigc3s3.1 Figure 3.3.1
normaltable Normal Distribution Table

--O--

onesampsgn One-Sample Sign Analysis

--P--

pcn Probability of Contaminated Normal (CDF)
percentciboot Percent Confidence Interval bootstrap
piest Estimation of Pi Using Binomial Experiment
piest2 Estimation of Pi by Monte Carlo Integration
plifetime Probability of Battery Lifetime
plogF Probability of Log Distribution
ploggamma PDF of Mixture Distribution
plotsulfur Plot Sulfurdioxide
pltlogF Plot Log Function
poisrand Simulating Poisson Processes
poissonci Confidence Interval for mean of of a Poisson Distribution
poissontable2 Poisson Distribution Table
psum Probability Outcomes for a Multinomial Trial

--Q--

qlaplace Laplace Quantiles
qlogF Quantile of Log Distribution
qqplotc4s2 Population Quantile Plots

--R--

rcn Random Contaminated Normal Deviates
rscn Random Sample from Contaminatied Normal Distribution

--S--

simplegame Simple Game for Estimation of Expected Gain

--T--

tpower2g2 Power Function Of The Two Sample Test
tpowerg Power of the One Sample t-Test
tpowerg2 Graphs a Two Sample T-Test
ttable t-Distribution Table

--W--

waldpois Wald Test Statistic
wil2powsim Wilcox Power Simulation

austinragotzy/mathstat documentation built on May 13, 2019, 11:30 a.m.