Software

Pruned_Bayes(2017)- [A Pruned, Recursive Solution to the Multiple Change Point Problem] – Programmed in Matlab

• A more efficient version of the Bayesian change point algorithm that uses a pruning procedure to reduce the number of calculations performed.
• Algorithm is quadratic in the distance between change points rather than quadratic in the total number of observations.
• Measure of divergence shows the approximate posterior distribution on the location of the change points is nearly identical to the exact posterior distribution
• Reference: Ruggieri, E. (2018) “A Pruned, Recursive Solution to the Multiple Change Point Problem,” Computational Statistics, 33(2), 1017-1045. doi: 10.1007/s00180-017-0756-9 .

CLT_Simulation(2016)- [Simulating the Central Limit Theorem] – Programmed in Matlab

• Simulator lets the user draw an arbitrary population distribution and then watch as the sampling distribution for the mean, median, or standard deviation grows in real time.
• Reference: Ruggieri, E. (2016), “Visualizing the Central Limit Theorem through Simulation,” PRIMUS. doi: 10.1080/10511970.2015.1094684

Bayes_Sequential_Chgpt(2016)- [Sequential Bayesian Change Point algorithm] – Programmed in Matlab

• An efficient algorithm for performing sequential Bayesian change point analysis using a linear regression model input by user
• Determines uncertainty estimates for the number and location of change points, or regime boundaries
• Reference: Ruggieri, E. and Antonellis, M. (2016), “An exact approach to sequential Bayesian change point detection,” Computational Statistics and Data Analysis 97, 71-86. doi: 10.1016/j.csda.2015.11.010

Bayes_Chgpt(2014)- [Bayesian Change Point algorithm] – Programmed in Matlab (I'm working on an R package)

• An efficient algorithm for performing a Bayesian change point analysis using a linear regression model input by user
• Determines uncertainty estimates for the number and location of change points, or regime boundaries
• Included in Acycle , a software package for the analysis of time series designed for paleoclimate research and education.
• Reference: Ruggieri, E. (2013), “A Bayesian Approach to Detecting Change Points in Climatic Records,” International Journal of Climatology. 33(2) 520-528. doi: 10.1002/joc.3447

EBIR(2012) - [Exact Bayesian Inference in Regression] – Programmed in Matlab

• An efficient algorithm for performing Bayesian variable selection and model averaging
• Calculates the posterior probability of a model given a data set and the marginal probability of including each of the predictor variables
• Also available as a webserver at: http://ccmbweb.ccv.brown.edu/ebir.html
• Reference: Ruggieri, E. and Lawrence, C.E. (2012), “On efficient calculations for Bayesian variable selection,” Computational Statistics and Data Analysis, 56: 1319-1332. doi:10.1016/j.csda.2011.09.026

Bayes_Chgpt_VS(2012) - [Bayesian Change Point and Variable Selection algorithm] – Programmed in Matlab

• Combines the Bayesian Change Point and EBIR algorithms into a single efficient algorithm
• Also available at website of Journal of Computational and Graphical Statistics once published
• Reference: Ruggieri E. and Lawrence, C.E. (2014), “The Bayesian Change Point and Variable Selection Algorithm: Application to the δ18O Record of the Plio-Pleistocene,” Journal of Computational and Graphical Statistics , 23 (1), 87-110. doi:10.1080/10618600.2012.707852

Change_Point (2009)– Programmed and Developed in Matlab with Graphical User Interface

• Calculates optimal placement of any number of change points, or regime boundaries, using least squares linear regression
• Generates sinusoidal or polynomial regression model or can have regression model input by user  
• Reference: Ruggieri, E., Herbert, T., Lawrence, K., and Lawrence, C.E. (2009), “The Change Point Method for Detecting Regime Shifts in Paleoclimatic Time Series: Application to δ18O Time Series of the Plio-Pleistocene,” Paleoceanography, 24, PA1204, doi:10.1029/2007PA001568

 

Note: All software is made available under the GNU Public license. Please cite the appropriate article if you use any of these software packages in your research.