Ryan Kelly

Recently Published

Big-ish Data Workflow in R
This article aims to replicate the recently (2015) plotly article in R. Link to article: Big data analytics with Pandas and SQLite Please make comments or suggestions via email, issues, or pull requests.
R for Interactive Reporting
Using dygraphs and DT to make interactive reports using R
Density Plot
Histogram Example
Client Histogram Sample
Non-Linear Models
Splines, Local Regression, Polynomial Regression, GAM
Support Vector Machines
Using caret and e1071. Start to finish: teaching the concepts to full examples.
Decision Trees
Resampling Methods
cross validation and bootstrap theory and examples
Auto Generate Markdown Tables
use knitr to beautify your table outputs in your reproducible research.
KNN, logistic regression, LDA, QDA, random forests examples using the Boston dataset
More time series analysis: Seasonal ARIMA models + forecasting.
Time series Analysis: Stationarity Smoothing methods
Intro to time series analysis
Lots of start-to-finish times series analysis examples. Very informative.
Forecasting with non-seasonal ARIMA models
ARIMA models for time series analysis
Linear Discriminant Analysis and Quadratic DA in R.
Classification: Logistic Regression
Classification: Logistic Regression
Start to Finish: Time Series Analysis
A few start to finish examples of time series analysis with ARIMA models
Seasonal ARIMA models
Model fitting and forecasting
Machine Learning 2
Mostly introduces the `caret` package in R, and how to apply it to solve some machine learning tools
Time Series Analysis 4
Introduction to forecasting with non-seasonal ARIMA models
Machine Learning: Initial Considerations
Material taken from the coursera class, link inside.
Time Series Analysis 3
AR, MA, ARMA, ARIMA models Diagnostics Examples
Time Series Analysis 2
Stationarity, ACF and CCF
Time Series Analysis 1
The basics of time series analysis
Time Series Analysis
Learning time series analysis in R