PHYSTAT 05
Abstracts
All abstracts are in Adobe PDF format
Random walks, a link between statistical, condensed matter, mathematical and particle Physics. Ali Alavi (Seyed Ali Asghar Alavi)
Application of machine learning tools to particle Physics P. Bargassa, S. Herrin, SJ Lee, P. Padley, R. Vilalta  Rice University and The University of Houston, USA
A note on Delta ln L = 1/2 errors Roger Barlow, Physics.org
Asymmetric Errors Roger Barlow, Physics.org
Bayesian Neural Networks P.C. Bhat (Fermi, Il USA), H.B. Prosper (Florida State University)
Regularized inversion methods and error bounds for general statistical inverse problems with application to density estimation of young massive cluster luminosities in the Antennae galaxies Dr. Nicolai Bissantz  University of Göttingen, Germany
Program for evaluation of the significance confidence intervals and limits by direct probabilities calculations S. Bityukov and various  Institute for high energy physics, Russia
The Bayesian effects in measurement of the astmmetry of Poisson flows S. Bityukov and various  Institute for high energy physics, Russia
Statistically dual distributions in statistical inference S. Bityukov and various  Institute for high energy physics, Russia
A new fast trackfit algorithm based on broken lines Volker Blobel  University of Hamburg, Germany
Sifting data in the real world M.M. Block  Department of Physics & Astronomy, Northwestern University, IL USA.
Maximal information analysis: I  various Wayne State plots and the most common likelihood principle G. Bonvicini, Wayne State University, Detroit
Least Squares Approach to the Alignment of the Generic High Precision Tracking System P. Brückman de Renstrom, S. Haywood  Univeristy of Oxford and Rutherford Appleton Laboratory, UK
Statistics in ROOT R. Brun, A. Kreshuk  CERN
CEDAR: Combined eScience Data Analysis Resource Andy Buckley  CEDAR, Durham, UK
BiasFree Estimation in Multicomponent Maximum Likelihood Fits with ComponentDependent Templates P. Catastini (Universita’ di Siena), G. Punzi (Scuola Normale Superiore)  INFN Pisa, Italy
Bayesian analysis at work: troublesome examples J. Charles & Various  France, Germany.
Restoration of Supersymmetry against arbitrary small quantum corrections using feedforward neural network Dr Ashish Chaturvedi
Likelihood Ratio Confidence Intervals with Bayesian Treatment of Systematic Uncertainties J. Conrad (CERN) & F. Tegenfeldt (ISU)
Generalized Frequentist Methods for Particle Physics Luc Demortier, The Rockefeller University
Bayesian Reference Analysis for Particle Physics Luc Demortier, The Rockefeller University
Application of a multidimensional wavelet denoising algorithum for the detention and characterization of astrophysical sources of Gamma rays. S.W.Digel, B.Zhang, J.Chiang, M.Fadili, J.L.Starck
x^{2} test for comparison of weighted and unweighted histograms N.D. Gagunashvili  University of Akureyri, Iceland
Unfolding with system identification N.D. Gagunashvili  University of Akureyri, Iceland
How to do BayesOptimal Classification with Massive Datasets: LargeScale Quasar Discovery A. Gray and Various  School of Computer Science, Carnegie Mello University, USA
GoodnessofFit Statistics: Power Comparisons M. Grazia Pia, B. Mascialino  INFN, Italy
An update on the GoodnessofFit Statistical Toolkit M. Grazia Pia, B. Mascialino  INFN, Italy
The Bayesian Approach to Setting Limits: What to Avoid Joel Heinrich  University of Pennsylvania
Examining the balance between optimising an analysis for best limit setting and best discovery potential G. Hill, J. Hodges, B. Hughey and M. Stamatikos  University of Wisconsin, USA.
Likelihood analysis and goodnessoffit for low countrate experiments A. Ianni  Laboratori Nazionali del Gran Sasso/INFN, Italy
Higher Criticism Statistic: Optimality and Applications in Cosmology and Astronomy Jiashun Jin  Department of Statistics Purdue University, IN USA.
Expected principal component analysis of cosmic microwave background anisotropies Samuel Leach, SISSAISAS, Italy Additional Information: http://xxx.soton.ac.uk/abs/astroph/0506390
New Developments of ROOT Mathematical Software Libraries Lorenzo Moneta  CERN
Confidence interval construction applied to an unfolding problem K. Muenich, G. Hill, W. Rhode and H. Geenen
StatPatternRecongnition: A C++ Package for Statistical Analysis of High Energy Physics Data Ilya Narsky  California Institute of Technology
Optimization of Signal Significance by Bagging Decision Trees Ilya Narsky  California Institute of Technology
Fitting boundary value problems Geoff Nicholls & Various  Department of Statistics, University of Oxford
sPLot; a statistical tool to unfold data distribitions M. Pivk (Cern) and F.R. Le Diberder (LAL Paris University, France)
Ordering Algorithms and Confidence Intervals in the Presence of Nuisance Parameters Giovanni Punzi  Scuola Normale Superiore and INFN  Pisa
A General Theory of Goodness of Fit in Likelihood Fits Rajendran Raja  Fermi Nartional Accelerator Lab, Batavia, IL
Calculation of errors in fitted quantities in likelihood fits Rajendran Raja  Fermi Nartional Accelerator Lab, Batavia, IL
The Boosting Technique for Particle Physics B.P.Roe, H.Yang and J.Zhu  University of Michigan, USA.
Limits and Confidence Intervals in the Presence of Nuisance Parameters Dr. Wolfgang Rolke, University of Puerto Rico  Mayaguez
Cosmological applications of Bayesian model selection techniques Roberto Trotta  Oxford Astrophysics & Royal Astronomical Society
The RooFit toolkit for data modeling W. Verkereke, NL
Signal Enhancement Using Multivariate Classification Techniques and Physical Constraints R.Vilalta, P. Sarda and Others  Houston University and Rice University
Goodnessoffit for sparce distributions in high energy physics. B.D. Yabsley, University of Sydney, Australia
Maximum Likelihood Parameter Inference from Lowe Statistics Data and Monte Carlo Simulation Dr Günter Zech, Germany
On Consistent and Calibrated Inference about the Parameters of Sampling Distributions Tomi Zivko, Jozef Stefan Institute, Ljubljana, Slovenia
Statistical Software Prof James Linneman, Michigan State University
