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"Statistical Techniques for Particle Physics" (4/4)
2009-02-05 11:00:00 (CET)
more...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will be to build up to techniques meant for dealing with problems of realistic complexity while maintaining a formal approach. I will also try to incorporate usage of common tools like ROOT, RooFit, and the newly developed RooStats framework into the lectures. The first lecture will begin with a review the basic principles of probability, some terminology, and the three main approaches towards statistical inference (Frequentist, Bayesian, and Likelihood-based). I will then outline the statistical basis for multivariate analysis techniques (the Neyman-Pearson lemma) and the motivation for machine learning algorithms. Later, I will extend simple hypothesis testing to the case in which the statistical model has one or many parameters (the Neyman Construction and the Feldman-Cousins technique). From there I will outline techniques to incorporate background uncertainties. If time allows, I will touch on the statistical challenges of searches for physics beyond the standard model and the look-elsewhere effect.
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"Statistical Techniques for Particle Physics" (3/4)
2009-02-04 11:00:00 (CET)
more...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will be to build up to techniques meant for dealing with problems of realistic complexity while maintaining a formal approach. I will also try to incorporate usage of common tools like ROOT, RooFit, and the newly developed RooStats framework into the lectures. The first lecture will begin with a review the basic principles of probability, some terminology, and the three main approaches towards statistical inference (Frequentist, Bayesian, and Likelihood-based). I will then outline the statistical basis for multivariate analysis techniques (the Neyman-Pearson lemma) and the motivation for machine learning algorithms. Later, I will extend simple hypothesis testing to the case in which the statistical model has one or many parameters (the Neyman Construction and the Feldman-Cousins technique). From there I will outline techniques to incorporate background uncertainties. If time allows, I will touch on the statistical challenges of searches for physics beyond the standard model and the look-elsewhere effect.
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"Statistical Techniques for Particle Physics" (2/4)
2009-02-03 11:00:00 (CET)
more...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will be to build up to techniques meant for dealing with problems of realistic complexity while maintaining a formal approach. I will also try to incorporate usage of common tools like ROOT, RooFit, and the newly developed RooStats framework into the lectures. The first lecture will begin with a review the basic principles of probability, some terminology, and the three main approaches towards statistical inference (Frequentist, Bayesian, and Likelihood-based). I will then outline the statistical basis for multivariate analysis techniques (the Neyman-Pearson lemma) and the motivation for machine learning algorithms. Later, I will extend simple hypothesis testing to the case in which the statistical model has one or many parameters (the Neyman Construction and the Feldman-Cousins technique). From there I will outline techniques to incorporate background uncertainties. If time allows, I will touch on the statistical challenges of searches for physics beyond the standard model and the look-elsewhere effect.
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"Statistical Techniques for Particle Physics" (1/4)
2009-02-02 11:00:00 (CET)
more...
This series will consist of four 1-hour lectures on statistics for particle physics. The goal will be to build up to techniques meant for dealing with problems of realistic complexity while maintaining a formal approach. I will also try to incorporate usage of common tools like ROOT, RooFit, and the newly developed RooStats framework into the lectures. The first lecture will begin with a review the basic principles of probability, some terminology, and the three main approaches towards statistical inference (Frequentist, Bayesian, and Likelihood-based). I will then outline the statistical basis for multivariate analysis techniques (the Neyman-Pearson lemma) and the motivation for machine learning algorithms. Later, I will extend simple hypothesis testing to the case in which the statistical model has one or many parameters (the Neyman Construction and the Feldman-Cousins technique). From there I will outline techniques to incorporate background uncertainties. If time allows, I will touch on the statistical challenges of searches for physics beyond the standard model and the look-elsewhere effect.
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MissingET Trigger
2007-12-20 15:30:00 (CET)
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MissingET Slice
2007-07-24 16:30:00 (CEST)
more...
Call +41 22 767 7000
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MissingET Slice
2007-07-10 16:30:00 (CEST)
more...
Call: +41 22 767 7000
ask for Atlas MissingET Trigger with Kyle Cranmer
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MissingET Slice
2007-06-19 17:00:00 (CEST)
more...
Call +41 22 767 7000
ask for "Atlas MissingET Trigger" or "Kyle Cranmer"
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The ATLAS Analysis Model
2005-07-14 08:30:00 (CEST)
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New measurement: Higgs to 4 taus
2009-11-03 17:20:00 (CET)
- CRANMER Kyle (Speaker)
- SPAGNOLO Paolo (Speaker)
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RooStats tutorials (hands-on session 2)
2009-10-16 11:00:00 (CEST)
- Cranmer Kyle (Speaker
, NYU)
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Introduction to advanced methods in RooStats
2009-10-16 10:30:00 (CEST)
- Cranmer Kyle (Speaker
, NYU)
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ATLAS Statistics Issues
2009-10-15 16:40:00 (CEST)
- Glen Cowan (Speaker)
- Kyle Cranmer (Speaker)
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Introduction to RooStats project
2009-10-15 09:00:00 (CEST)
- Cranmer Kyle (Speaker
, NYU)
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Introduction and Announcements
2009-08-03 09:05:00 (EDT)
- Cranmer Kyle (Speaker
, NYU)
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Top and Higgs combinations with RooStats
2009-07-08 11:00:00 (CEST)
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Status of RooStats
2009-07-08 09:30:00 (CEST)
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Feldman Cousins tools probably
2009-04-30 15:50:00 (CEST)
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Bernstein corrections in RooStats
2009-04-30 15:30:00 (CEST)
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Discussion: Met Observables
2009-04-28 15:10:00 (CEST)
- Cranmer Kyle (Speaker
, NYU)
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Distributed analysis with PROOF in ATLAS Collaboration
2009-03-24 14:20:00 (CET)
- Majewski Stephanie (Author
, Brookhaven National Lab)
- Benjamin Doug (Author
, Duke University)
- Shibata Akira (Author
, New York University)
- Ye Shuwei (Author
, Brookhaven National Lab)
- Tarrade Fabien (Author
, New York University)
- Cranmer Kyle (Author
, New York University)
- Mellado Bruce (Author
, University of Wisconsin, Madison)
- Wenaus Torre (Author
, Brookhaven National Lab)
- Ernst Michael (Author
, Brookhaven National Lab)
- Guan Wen (Author
, University of Wisconsin, Madison)
- Carillo Montoya German (Author
, University of Wisconsin, Madison)
- Ito Hironori (Author
, Brookhaven National Lab)
- Rind Ofer (Author
, Brookhaven National Lab)
- Maeno Tadashi (Author
, Brookhaven National Lab)
- Xu Neng (Author
, University of Wisconsin, Madison)
more...
The Parallel ROOT Facility - PROOF is a distributed analysis system which allows to exploit inherent event level parallelism of high energy physics data.
PROOF can be configured to work with centralized storage systems, but it is especially effective together with distributed local storage systems - like Xrootd, when data are distributed over computing nodes.
It works efficiently on different types of hardware and scales well from a multi-core laptop to large computing farms.
From that point of view it is well suited for both large central analysis facilities and Tier 3 type analysis farms.
PROOF can be used in interactive or batch like regimes. The interactive regime allows user to work with typically distributed data from ROOT command prompt and get a real time feedback on analysis progress and intermediate results.
We will discuss our experience with PROOF in the context of ATLAS Collaboration distributed analysis.
In particular we will discuss PROOF performance in various analysis scenarios and in multi-user, multi-session environment. We will also describe PROOF integration with ATLAS distributed data management system and prospects of running PROOF on geographically distributed analysis farms.
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ATLAS Roostats status
2008-09-25 17:10:00 (CEST)
- Kyle Cranmer (ATLAS) (Speaker)
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RooStats Developments
2008-07-29 14:50:00 (CEST)
- Kyle Cranmer (ATLAS) (Speaker)
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EventView news: Factorization, ARA, etc.
2008-06-18 16:50:00 (CEST)
- Cranmer Kyle (Speaker
, NYU)
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EV news: Inserters, Modularization and POOL/ROOT compliant persistification
2008-04-30 11:40:00 (CEST)
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5.19/04 dev release scheduled for May 7
2008-04-18 11:30:00 (CEST)
more...
-expect new roofit/roostats package from Kyle Cranmer and Wouter Verkerke
-material in branches must be moved before middle of next week
-developments by Ilka/Roj will be introduced after the release
-fixes to get "make static" and the code checker working again
-THtml must be modified to support the new dir structure (urgent)
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User Data on DPDs
2008-02-28 09:30:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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User Data (analysis data) and EV persistification
2008-01-30 16:20:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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User Data (analysis data)
2008-01-16 16:10:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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Introduction, Announcements, Planning, & Priorities
2007-12-20 15:30:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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Physics Analysis
2007-12-12 18:00:00 (CET)
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Persistification of EventView and ParticleView
2007-12-05 16:30:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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user data issues II
2007-11-29 09:40:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
- Farbin Amir (Speaker
, European Organization for Nuclear Research (CERN))
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EventView
2007-11-14 13:45:00 (CET)
- Cranmer Kyle (Speaker
, NYU)
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