R

Master's Project: Reliability Estimation in Series Systems

My master's project on maximum likelihood estimation for series systems with right-censored and masked failure data.

algebraic.dist

Algebra over Probability Distributions

algebraic.mle

Algebraic Maximum Likelihood Estimators

compositional.mle

Compositional Maximum Likelihood Estimation

femtograd

Automatic Differentiation for Statistical Computing

flexhaz

Dynamic Failure Rate Distributions for Survival Analysis

hypothesize

Consistent API for Hypothesis Testing

kofn

Component Lifetime Estimation from k-out-of-n System Data

likelihood.model

Likelihood-Based Statistical Inference in the Fisherian Tradition

maskedcauses

Likelihood Models for Systems with Masked Component Cause of Failure

maskedhaz

Masked-Cause Likelihood Models for DFR Series Systems

nabla

Exact Derivatives via Automatic Differentiation

serieshaz

Series System Distributions from Dynamic Failure Rate Components

Masked Failure Data: Looking Back, Looking Forward

A retrospective on three years of building R packages and writing papers for masked series system reliability, and what comes next.

Observation Functors: Composable Censoring for Series System Simulation

Observation functors in maskedcauses: composable functions that separate the data-generating process from the observation mechanism, enabling mixed-censoring simulation and verified Monte Carlo studies.

maskedcauses: Maximum Likelihood Estimation for Masked Series System Failures

The maskedcauses R package for MLE in series systems with masked component failures, built on composable likelihood contributions and validated through simulation.

Graduate Statistics Problem Sets

My graduate coursework from SIUe's math program is up: time series, regression, computational stats, multivariate analysis, and statistical methods.

hypothesize: Now on CRAN

My R package for hypothesis testing, hypothesize, is now available on CRAN.

Likelihood Models for Series Systems with Masked Component Failure Data: An R Package for Maximum Likelihood Estimation

mdrelax: When Masking Conditions Don't Hold

Extending masked failure data analysis when the standard C1-C2-C3 masking conditions are violated.

Reliability Estimation in Series Systems Maximum Likelihood Techniques for Right-Censored and Masked Failure Data

likelihood.model: Composable Likelihood Models in R

A generic R framework for composable likelihood models. Likelihoods are first-class objects that compose through independent contributions.

hypothesize: A Consistent Interface for Statistical Tests

An R package that gives hypothesis tests a consistent interface. Every test returns the same structure. You can write generic code that works across all of them.

STAT 581 - Statistical Methods - SIUe - Fall 2021

Problem sets for STAT 581 - Statistical Methods at SIUe, taught by Dr. Neath during Fall 2021.

Statistical Methods - STAT 581 - Exam 1

An experiment is conducted to study the effect of fitness level on ego > strength. Random samples of college faculty members are selected from each

Statistical Methods - STAT 581 - Exam 2

A randomized complete block design is used to study the effect of caliper on the measured diameters

Statistical Methods - STAT 581 - Problem Set 1

An experiment is designed to investigate whether the time to drill holes in rock holes using wet or dry drilling.

Statistical Methods - STAT 581 - Problem Set 2

A product developer is investigating the tensile strength of a new synthetic fiber that will be used to make cloth for men’s shirts.

Statistical Methods - STAT 581 - Problem Set 3 a

An experiment is conducted to study the effect of drilling method on drilling time. Each method (dry drilling, wet drilling) is used on $n = 12$ rocks.

Statistical Methods - STAT 581 - Problem Set 3 b

An experiment to compare a new drug to a standard is in the planning stages. The response variable of interest is the clotting time (in minutes) of blood

Statistical Methods - STAT 581 - Problem Set 4

The insulating life of protective fluids at an accelerated load is being studied. The experiment has been performed for four types of fluids, with $n = 5$

Statistical Methods - STAT 581 - Problem Set 5

A factorial experiment is used to develop a nitride etch process on a single wafer plasma etching tool.

Statistical Methods - STAT 581 - Problem Set 6

A soft drink bottler is interested in studying the effects on a filling process. A factorial experiment is run using three factors: percent carbonation (in %),

Statistical Methods - STAT 581 - Problem Set 7

A paired comparisons design is used to study the effect of machine operator on > the measured running time (in secs.) of a fuse. A sample of $n = 10$ fuses is

Statistical Methods - STAT 581 - Problem Set 8

An experiment is designed to test for systematic differences in the hardness > measurements provided by two devices (fixed effect, factor $A$).

Statistical Methods - STAT 581 - Problem Set 9

The surface finish of metal parts made on $a=4$ machines is under > investigation. > Each machine can be run by one of $b=3$ operators.

Computational Statistics - SIUe - STAT 575 - Problem Set 2

This problem set covers the E-M algorithm for right-censored normal data with known variance.

SIUe - Computational Statistics (STAT 575) - Problem Set 4

This problem set covers sampling from a Gamma distribution using Metropolis-Hastings and acceptance-rejection methods.

flexhaz: Specify the Hazard Function Directly

An R package for specifying hazard functions directly instead of picking from a catalog of named distributions. You write the hazard. It handles the rest.

algebraic.mle: MLEs as Algebraic Objects

An R package that treats MLEs as algebraic objects. They carry Fisher information, compose through independent likelihoods, and propagate uncertainty correctly.

Discrete Multivariate Analysis - STAT 579 - Exam 2

Discrete multivariate analysis exam covering log-linear models and categorical data analysis.

Discrete Multivariate Analysis - STAT 579 - Final Exam

Final exam for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 10

Problem set 10 for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 5

Problem set 5 for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 6

Problem set 6 for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 7

Problem set 7 for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 8

Problem set 8 for discrete multivariate analysis.

Discrete Multivariate Analysis - STAT 579 - Problem Set 9

Problem set 9 for discrete multivariate analysis.

STAT 478 - Time Series Analysis - SIUe - Spring 2021

Problem sets for STAT 478 - Time Series Analysis at SIUe, taught by Dr. Beidi during Spring 2021.

STAT 579 - Discrete Multivariate Analysis - SIUe - Spring 2021

Problem sets for STAT 579 - Discrete Multivariate Analysis at SIUe, taught by Dr. Andrew Neath during Spring 2021.

Time Series Analysis - STAT 478 - Exam 1

Time series analysis exam covering ARMA processes and model identification.

Time Series Analysis - STAT 478 - Exam 2

Time series analysis coursework.

Time Series Analysis - STAT 478 - Final Exam

Final exam for time series analysis course.

Time Series Analysis - STAT 478 - Problem Set 3

Problem set 3 for time series analysis.

Time Series Analysis - STAT 478 - Problem Set 4

Problem set 4 for time series analysis.

Time Series Analysis - STAT 478 - Problem Set 5

Problem set 5 for time series analysis.

Time Series Analysis - STAT 478 - Problem Set 6

Problem set 6 for time series analysis.

Time Series Analysis - STAT 478 - Project

Time series analysis project.

algebraic.dist: Distributions as Algebraic Objects in R

An R package that treats probability distributions as algebraic objects. They compose through standard operations. The algebra preserves distributional structure.

Building R Packages for Statistical Inference

I'm building R packages for reliability analysis, not just using other people's. R's strengths for statistical computing are real, and building packages forces you to understand the theory.