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Summer School in Statistics for Astronomers & Physicists
June 5-17, 2005

Photographs

 
All morning sessions are in Room 124, Thomas Building
All afternoon Computer lab sessions are in Room 71, Willard Building
     (Eric Feigelson, Murali Haran, David Hunter, Derek Young, Hyunsook Lee)

June 4, 2005, 8:00 p.m. - 9:30 p.m.  Reception at Comfort Suites


Statistical Inference for Astronomers (June 5-10, 2005 - Penn State)
 
June 5, 2005 (Sunday)  Introduction and descriptive statistics
    7:45 a.m. -  9:00 a.m.  Registration and issue of computer accounts (327 Thomas)
    9:00 a.m. -  9:10 a.m.  Introduction to CASt (G. J. Babu)
    9:10 a.m. - 10:00 a.m.  Introduction to astrostatistics (Eric Feigelson)
                  Break (327 Thomas)
   10:30 a.m. - 12:15 p.m. Descriptive statistics, box plots and histograms (William Harkness)

   12:15 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:30 p.m.  Computer lab session (71 Willard)
                  Walk to Thomas building and break (327 Thomas)
    4:00 p.m. -  5:15 p.m.  Correlation & regression, regression model in matrix terms, multiple regression and linear models (William Harkness, 201 Thomas)
    5:15 p.m. -  5:30 p.m.  Evaluation (Eric Feigelson, 201 Thomas)


June 6, 2005 (Monday)  Probability and basic statistical inference (Donald Richards)
    8:45 a.m. - 10:30 a.m.  Laws of probability, Bayes' theorem and the Central Limit Theorem
                  Break (327 Thomas)
   11:00 a.m. - 12:30 p.m.  Estimation, confidence intervals and tests of hypotheses

   12:30 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:30 p.m.  Computer lab session (71 Willard)
                  Walk to Thomas building and break (327 Thomas)
    4:00 p.m. -  5:00 p.m.  Virtual observatories (Ajit Kembhavi, 201 Thomas)
    5:00 p.m. -  5:30 p.m.  Evaluation (Eric Feigelson, 201 Thomas)


June 7, 2005 (Tuesday)  Maximum likelihood estimation
    8:45 a.m. - 10:30 a.m.  MLEs, Cramer-Rao inequality, and Bayesian information criterion (Donald Richards)
                  Break (327 Thomas)
   11:00 a.m. - 12:30 p.m.  Model selection and evaluation, goodness-of-fit tests and likelihood ratio tests (C. R. Rao)

   12:30 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:00 p.m.  Computer lab session (71 Willard)
                  Walk to Thomas building and Break (327 Thomas)
    3:30 p.m. -  5:30 p.m.  Multivariate analysis: Multivariate normal, MLE, Mahalanobis distance, and discriminant analysis  (T. Krishnan, 201 Thomas)
    5:30 p.m. -  5:45 p.m.  Evaluation (Eric Feigelson, 201 Thomas)


June 8, 2005 (Wednesday)  Nonparametric statistics (Steven Arnold)
    8:45 a.m. - 10:15 a.m.  One-sample, k-sample, and bivariate tests
                  Break (327 Thomas)
   10:45 a.m. - 12:15 p.m.  Robust methods

   12:15 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  2:45 p.m.  Cluster analysis (C. R. Rao, 11 Life Sciences Building)
                  Break (327 Thomas) and walk to Willard building
    3:15 p.m. -  5:15 p.m.  Computer lab session (71 Willard)
    5:15 p.m. -  5:30 p.m.  Evaluation (Eric Feigelson, 71 Willard)

    6:00 p.m. -  8:00 p.m.  Dinner at Cafe Laura (Mateer Building)


June 9, 2005 (Thursday)  Resampling and Monte Carlo methods
    8:45 a.m. - 10:15 a.m.  Resampling (G. J. Babu)
                  Break (327 Thomas)
   10:45 a.m. - 12:15 p.m.  Old-fashioned Monte Carlo methods (Steven Arnold)

   12:15 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:30 p.m.  Computer lab session (71 Willard)
                  Walk to Thomas building and Break (327 Thomas)
    4:00 p.m. -  5:30 p.m.  Bayesian-Frequentist Cross-Fertilization (Two lectures): Bayesian Inference in a Nutshell, and The Perils & Promise of Statistics With Large Data Sets & Complicated Models (Tom Loredo, 201 Thomas)
    5:30 p.m. -  5:45 p.m.  Evaluation (Eric Feigelson, 201 Thomas)


June 10, 2005 (Friday)
    8:45 a.m. - 10:15 a.m.  Poisson & Gaussian processes (Donald Richards)
                  Break (327 Thomas)
   10:45 a.m. - 12:15 p.m.  Multivariate analysis, continued (T. Krishnan)
   12:15 p.m. - 12:40 p.m.  Evaluation (Eric Feigelson, 124 Thomas)

June 11, 2005 (Saturday)  4:00 p.m.  -  8:00 p.m.  Picnic at the residence of William Harkness (Yildiz Park) 1877 Millson Circle, State College



The following two short courses are designed for astronomers who have attended the "Statistical Inference for Astronomers" course or have a more extensive statistical background.

Spatial Processes and Image Analysis
(
June 12-14, 2005 - Penn State)
     (Yassir Moudden and Sandrine Pires)

June 12, 2005 (Sunday)
    8:45 a.m. - 10:30 a.m.  Basic models and tools in signal and image processing
                  Break (327 Thomas)
   11:00 a.m. - 12:30 p.m.  Multiscale Transforms (wavelet, ridgelet, curvelet)

   12:15 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:00 p.m.  Computer Lab: Wavelet Transform implementation
                  Break (71 Willard)
    3:30 p.m. -  5:00 p.m.  Computer Lab: Wavelet Transform properties
    5:00 p.m. -  5:15 p.m.  Evaluation (G. J. Babu, 71 Willard)


June 13, 2005 (Monday)
    8:45 a.m. - 10:30 a.m.  Multiresolution analysis and wavelet bases
                  Break (327 Thomas)
   11:00 a.m. - 12:30 p.m.  Image restoration, noise models, detection and deconvolution

    12:15 p.m. -  1:30 p.m.  Lunch break

     1:30 p.m. -  3:00 p.m.  Computer Lab session: Wavelet Transform applications I
                   Break (71 Willard)
     3:30 p.m. -  5:00 p.m.  Computer Lab session: Wavelet Transform applications II
     5:00 p.m. -  5:15 p.m.  Evaluation (G. J. Babu, 71 Willard)


June 14, 2005 (Tuesday)
     8:45 a.m. - 10:30 a.m.  Multidimensional data analysis
                   Break (327 Thomas)
   11:00 a.m. - 12:30 p.m.  Multidimensional data analysis (continued)

   12:15 p.m. -  1:30 p.m.  Lunch break

     1:30 p.m. -  3:00 p.m.  Computer Lab session: Ridgelet and Curvelet Transforms
     3:30 p.m. -  3:45 p.m.  Evaluation (G. J. Babu, 71 Willard)

     6:00 p.m. -  8:00 p.m.  Dinner at Cafe Laura (Mateer Building)



Computational Algorithms for Astrostatistics (June 15-17, 2005 - Penn State)

June 15, 2005 (Wednesday)
    9:00 a.m. - 10:30 a.m.  Principles of statistical algorithms (T. Krishnan)
                  Break (327 Thomas)
   11:00 a.m. - 12:30 a.m.  Markov chain Monte Carlo algorithms, including Metropolis-Hastings and Gibbs sampler (Steven Arnold)

   12:30 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  3:30 p.m.  Computer lab session: MCMC (Murali Haran and Derek Young, 71 Willard)
    3:30 p.m. -  3:45 p.m.  Evaluation (Eric Feigelson, 71 Willard)


June 16, 2005 (Thursday)
    9:00 a.m. - 10:30 a.m.  EM algorithm (T. Krishnan)
                  Break (327 Thomas)
   11:00 a.m. - 12:30 a.m.  Homotopy continuation algorithms (Max Buot and Donald Richards)

   12:30 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  2:30 p.m.  Computer lab session: Discriminant analysis and EM algorithm  (T. Krishnan and Hyunsook Lee, 71 Willard)
    2:30 p.m. -  4:00 p.m.  Computer lab session (Max Buot, 71 Willard)
    4:00 p.m. -  4:15 p.m.  Evaluation (Eric Feigelson, 71 Willard)


June 17, 2005 (Friday)
    9:00 a.m. - 10:30 a.m.  Genetic algorithms (Max Buot and Donald Richards)
                  Break (327 Thomas)
   11:00 a.m. - 12:30 a.m.  Cluster analysis (Max Buot and Donald Richards)

   12:30 p.m. -  1:30 p.m.  Lunch break

    1:30 p.m. -  2:30 p.m.  Computer lab session: Genetic algorithms (Max Buot, 71 Willard)
    2:30 p.m. -  2:45 p.m.  Evaluation (Eric Feigelson, 71 Willard)


Forthcoming 2006 Penn State Conference:

    Statistical Challenges in Modern Astronomy IV. The fourth in a series of interdisciplinary international conferences, Statistical Challenges in Modern Astronomy, will be held during June 12-15, 2006 at the Pennsylvania State University, University Park, USA.

Future courses:

The following courses are planned for 2006 and 2007. Some of these will be offered at the Statistical and Applied Mathematical Sciences Institute (SAMSI) in the Research Triangle Park, NC in 2006. 

Bayesian Inference for Astronomers
(Spring 2006 -  SAMSI)

Multivariate Statistical Analysis for Astronomers (Spring/Summer 2007)
  • Organization and visualization of multivariate data
  • Inference for mean vectors, covariance matrices & multinormal distributions
  • Multivariate linear regression, analysis of variance and covariance
  • Principal component analysis (PCA)
  • Clustering methods: agglomerative, k-means, decision trees, MLE
  • Missing data
Time Series Analysis (Summer 2007 - Penn State)
  • Basic time series models
  • Exploratory data analysis, variability and constancy
  • Autocorrelation & cross-correlation
  • Time series regression: ARMA, ARIMA, GARCH models
  • Spectral analysis: FFT, filtering, (multi)tapering, period searching
  • Maximum likelihood methods, state space models
  • Kalman filter, smoothing procedures

NSFDepartment of StatisticsEberly College of ScienceDepartment of Astronomy and Astrophysics