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## Tutorials and Schools- R Tutorials (Penn State - IIA Summer School 2008)
- Summer School 2007, R tutorials
- Markov chain Monte Carlo Examples using R
- Tutorials and Opening Workshop for Astrostatistics Program at SAMSI, January 2006
- Summer School 2006
- R tutorials, 2006 Exercises in R, an open-source environment for statistical computing and graphics
- Summer School 2005
## MSMA datasets
## Astronomical datasets for statistical analysis
- Univariate datasets
- Distance to the LMC (N=1, repeated measurements, measurement errors)
- Asteroid densities (N=28, density estimation, measurement errors)
- Globular cluster luminosity function (N~81+360, normal model, truncation, 2-sample test)
- Planetary nebula luminosity function (N~238+45+101+59, k-sample test, nonparametrics, semi-parametrics, truncation)
- Censored datasets
- Planet host stars (N=39 and 29;
survival analysis, Kaplan-Meier, 2-sample, linear regression, censoring)
- Multivariate datasets
- Shapley galaxy redshift catalog (N=4,315, p=5, spatial point process, hierarchical clustering, wavelets, measurement errors)
- Hipparcos
star catalog (N=2,719, p=8, multivariate clustering, mixture
models, regression, measurement errors, outliers)
- COMBO-17
galaxy photometric catalog
(N=3,462, p=65, multivariate analysis, regression, clustering,
truncation)
- SDSS
quasar catalog (N=46,420, p=23, multivariate analysis, regression,
clustering, measurement errors, truncation, )
- New SDSS
quasar catalog (N=77,429, p=18, multivariate analysis, regression,
clustering, measurement errors, truncation, )
- Signal processing (spectra
and time series)
- Chandra Orion star flares (N=209, 678 and 14,258, time series analysis, inhomogeneous Poisson process, Bayesian modeling, wavelets)
- Extrasolar planet
radial velocities (N=17, 52, 138, periodicity detection,
nonlinear regression, parameter estimation, measurement error, Bayesian
modeling)
- Galaxy spectra (feature characterization, parameter estimation)
- Quasar absorption spectra (feature characterization, parameter estimation, normal mixture model)
- Model selection
- Gamma-ray burst afterglow modelling (N=63, p=2, linear regression, breakpoints, measurement errors, model elaboration and parsimony)
- Images
- Chandra star cluster (Poisson signal detection, Poisson image deconvolution, parameter estimation)
Questions about these datasets may be directed to Eric Feigelson |