TAMU Fall 2015 Astrostatistics

Lecture 26 (December 1)

• Local Linear Embedding
• Presentation (Katelyn Stringer)
• Code (Nayan Chaudhary: LLE applied to project 4 data, requires IPython notebook)

Lecture 25 (November 24)

• Multidimensional Scaling (code)
• Splines (code)

Lecture 24 (November 19)

• GeneticAlgorithm.pdf
• Making Composites
• composites.pdf (Slides)
• composites.Rnw (Latex and R for making slides)
• Background on Functional Data
• fdata.pdf (Slides)
• fdata.Rnw (Latex and R for making slides)

Lecture 23 (November 17)

• Fisher Matrix and Systematic Errors
• Findings of the Joint Dark Energy Mission
• Systematic Error
• Fisher Matrix
• Principal Components Analysis
• pca.pdf (Presentation)
• pca.Rnw(R and Latex for Making Presentation)

Lecture 22 (November 12)

• Clustering
• clustering.pdf (Clustering Slides)
• clustering.Rnw (Latex + R for making slides)

Lecture 21 (November 10)

• Tricks for Image Analysis (Yi Yang Presentation)
• Project 4
• Description and Data (~ 40MB)
• Background (Ben Forrest Presentation)

Lecture 20 (November 5)

• Neural Networks in Source Extractor (Code and Presentation)

Lecture 19 (November 3)

• R Code for fitting Supernovae data
• Distances in Cosmology

Lecture 18 (October 29)

• MCMC for Bayesian Inference (Code and Slides)

Lecture 17 (October 27)

• Basics of Bayesian Inference
• Monte Carlo Methods in Statistics (Code and Slides)

Lecture 16 (October 22)

• Regression in Astronomy II Slides

Lecture 15 (October 20)

• Regression in Astronomy Slides

Lecture 14 (October 15)

• Project 3 Description

Lecture 13 (October 13)

• Constructing Catalogs from Images: DS9 and Source Extractor

Lecture 12 (October 8)

• Image Subtraction, Point Spread Functions, Convolution, and Deconvolution

Lectures 10 / 11 (October 1 and 6)

• Nadaraya Watson Non--parametric period estimation
• Non parametric regression example with Nadaraya Watson
• Tutorial on Nonlinear Regression in Astronomy
• Non--parametric density estimation and regression with measurement error

Lecture 9 (September 29)

• Summary of Statistical Methods by Particle Physicists
• 3D Plot of Cepheid light curves as a function of period (requires WebGL)
• cepheids_3d.R (code for making 3d scatterplot)
• iplots.R (interactive plotting in R using SDSS variables)

Lecture 8 (September 24)

• Calling Fortran, C, and C++ Functions from R, presentation by Shiyuan
• Parallelizing Code in R
• Variable Star Classification Code and Presentation

Lecture 7 (September 22)

• Cepheid PL Relation presentation by Wenlong Yuan

Lecture 6 (September 17)

• period_estimation.R
• sample light curve for period estimation
• Exoplanet Detection and Box Least Squares presentation by Ryan Oelkers

Lecture 5 (September 15)

• Project 2 Description and Data (~ 250MB)
• Bootstrap for the Bernoulli
• Background on Photometry

Lecture 4 (September 10)

• Kolmogorov-Smirnov Test Simulation
• Uniform Sampling Distribution Simulation

Lecture 3 (September 8)

• Notice: Statistical Challenges in Modern Astronomy Conference June 6-10 scma6.org
• Notice: 2016-2017 Program on Astrostatistics at SAMSI
• Notice: Short Courses on High Performance Computing at TAMU

Lecture 2 (September 3)

• homework1.pdf
• Solutions to Homework 1, Question 1
• RiceDistribution.pdf (description of astronomical coordinate system)

Lecture 1 (September 1)

• syllabus.pdf
• Examples of Statistical Challenges in Astronomy
• rdemo.R
• A Framework for Inference in Astrophysics