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101. http://hea-www.harvard.edu/AstroStat/Stat310_0910/xx_20100420.pdf
... Estimates of parameters with noisy data are usually correlated. ... S1j , T1 , 1 , C1 ), · · · , (Snj , Tn , n , Cn ) 2 Step IV : µc , c |C1 , · · · , Cn 2 Step V : |1 , · · · , J n n Step VI : A|B , T1 , · · · , Tn , 1 , · · · , Step VII : B |A, T1 , · · · , Tn , 1 , · · · , logo 10/20 Graphical Illustration of Step I (A,B) T 1 T i j f f 1 i 11 1 f i1 1j C 1 c C i logo 11/20 Graphical Illustration of Step II (A,B) T 1 T i j f f 1 i 11 1 f i1 1j C 1 c C i ... logo 20/20 ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_0910/xx_20100420.pdf -- 620.1 Кб -- 20.04.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_0910/xx_20100420.pdf -- 620.1 Кб -- 20.04.2010
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_0910/xx_20100420.pdf -- 620.1 Кб -- 20.04.2010
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102. AstroStat Talks 2010-2011
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/ -- 24.4 Кб -- 01.10.2012
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ -- 24.4 Кб -- 01.10.2012
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[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ -- 24.4 Кб -- 01.10.2012
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/ -- 24.4 Кб -- 01.10.2012
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103. http://hea-www.harvard.edu/AstroStat/Stat310_1011/ad_20110419.pdf
... memb ers of the CAUSTIC Group www.dfg.unito.it/ricerca/caustic Cambridge, April 19th 2011 SCIENTIFIC BACKGROUND Observations of SNae : Interpretation in the CDM model Alternative cosmological models: Conformal gravity and kinematic conformal gravity GRBs as cosmological probes: Bayesian approach BAYESIAN ANALYSIS Parameter forecasts (posterior probability): Likelihood and priors ... Constitution set of Hicken et al 2009) Bayesian parameter estimation again.. ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/ad_20110419.pdf -- 2896.9 Кб -- 19.04.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ad_20110419.pdf -- 2896.9 Кб -- 19.04.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/ad_20110419.pdf -- 2896.9 Кб -- 19.04.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ad_20110419.pdf -- 2896.9 Кб -- 19.04.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/ad_20110419.pdf -- 2896.9 Кб -- 19.04.2011
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104. http://hea-www.harvard.edu/AstroStat/Stat310_1011/ds_20110329.pdf
Automatic Classification of Sunspot Groups Using SOHO/MDI Magnetogram and White Light Images David Stenning March 29, 2011 1 Introduction and Motivation Although solar data is being generated at an unprecedented rate, the majority of sunspot classification is done manually by experts. ... This is to smooth the "white" areas in the magnetograms. ... Left: Inverse Magnetogram Right: "Opened" Inverse Magnetogram 6 Using the cleaned images, sunspot active-region "seeds" are obtain by thresholding. ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/ds_20110329.pdf -- 635.7 Кб -- 29.03.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ds_20110329.pdf -- 635.7 Кб -- 29.03.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/ds_20110329.pdf -- 635.7 Кб -- 29.03.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/ds_20110329.pdf -- 635.7 Кб -- 29.03.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/ds_20110329.pdf -- 635.7 Кб -- 29.03.2011
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105. http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_fap_20100927.pdf
... Simple X-ray Aperture Photometry Problem : Determine source intensity s and errors for an unresolved (point) x-ray source Know: · Number of counts , C, in source aperture (solid green ellipse) · Number of counts , B, in background aperture (dashed green elliptical annulus) · Areas As and Ab of source and background apertures · f = psf(x,y)dx dy over source aperture · g = psf(x,y)dx dy over background ... What happens if the single observation pdf 's are distinct? ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_fap_20100927.pdf -- 133.0 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_fap_20100927.pdf -- 133.0 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_fap_20100927.pdf -- 133.0 Кб -- 27.09.2010
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_fap_20100927.pdf -- 133.0 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_fap_20100927.pdf -- 133.0 Кб -- 27.09.2010
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106. http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_jpb_20100927.pdf
... Do weaker flares have the same distribution? Sunday, September 26, 2010 Data from XRT on Hinode Difficulty: Detecting flare events in the presence of variable background Sunday, September 26, 2010 Flare Detection Strategies Currently we use 2 detection methods based on * time derivatives * segmenting based on significant minima and use simulated lightcurves to optimize parameter values. ... Sunday, September 26, 2010 black = observed, blue = best match Is this alpha=1.8 or alpha=2.5? ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_jpb_20100927.pdf -- 648.4 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_jpb_20100927.pdf -- 648.4 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_jpb_20100927.pdf -- 648.4 Кб -- 27.09.2010
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_jpb_20100927.pdf -- 648.4 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_jpb_20100927.pdf -- 648.4 Кб -- 27.09.2010
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107. http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_ksm_20100927.pdf
Hierarchical Bayesian Models for Type Ia SN Light Curves, Dust and Cosmic Distances Kaisey S. Mandel Harvard University 27 September 2010 Monday, September 27, 2010 1 Hierarchical Brings deep knowledge from data Distant star glows, fades. Bob Kirshner Monday, September 27, 2010 2 Cosmological Energy Content Monday, September 27, 2010 3 !" ... 7 Monday, September 27, 2010 AAS 215 AAS 215 *+,+-./ ... Host Galaxy Dust: extinction and reddening. ... 19 Monday, September 27, 2010 19 ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/haiku_ksm_20100927.pdf -- 1968.3 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_ksm_20100927.pdf -- 1968.3 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_ksm_20100927.pdf -- 1968.3 Кб -- 27.09.2010
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/haiku_ksm_20100927.pdf -- 1968.3 Кб -- 27.09.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/haiku_ksm_20100927.pdf -- 1968.3 Кб -- 27.09.2010
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108. http://hea-www.harvard.edu/AstroStat/Stat310_1011/nms_20110208.pdf
... n For illustration, examine a coarsened (256 в 256) set of images, with 3 clusters Clustering AIA data Clusters in log Y space Clusters in Y /n space Distribution of pixels in each cluster Distribution of pixels in each cluster Simulated Data Simulated Temperature Distributions 4 5 6 logT 7 8 9 Simulated Data Simulated Data Simulated Data Simulated Data Simulated Data: Results Simulated Data: Results Simulated Data: Results Simulated Data: Results How to make images of results more meaningful? ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/nms_20110208.pdf -- 2058.3 Кб -- 08.02.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/nms_20110208.pdf -- 2058.3 Кб -- 08.02.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/nms_20110208.pdf -- 2058.3 Кб -- 08.02.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/nms_20110208.pdf -- 2058.3 Кб -- 08.02.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/nms_20110208.pdf -- 2058.3 Кб -- 08.02.2011
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109. http://hea-www.harvard.edu/AstroStat/Stat310_1011/pb+is_20110712.pdf
... Run a detection algorithm to extract `sources' 3. ... Low intensity sources 2. ... Key Ideas Our goals: Provide a complete analysis, accounting for all detector effects (especially those leading to unobserved sources ) Allow for the incorporation of prior information Investigate parametric forms (testing) for log N - log S (e.g., broken power-laws) Investigate the data -prior inferential limit (e.g., for which Smin does the information come primarily from the model and not the data ) ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/pb+is_20110712.pdf -- 1244.9 Кб -- 12.07.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/pb+is_20110712.pdf -- 1244.9 Кб -- 12.07.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/pb+is_20110712.pdf -- 1244.9 Кб -- 12.07.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/pb+is_20110712.pdf -- 1244.9 Кб -- 12.07.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/pb+is_20110712.pdf -- 1244.9 Кб -- 12.07.2011
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110. http://hea-www.harvard.edu/AstroStat/Stat310_1011/vk_20101109.pdf
logN-logS A Measuring Stick for the Universe Vinay Kashyap (CfA) Tuesday , November 9, 2010 log10(N S)-log10(S) cumulative number of sources detectable at a given telescopic sensitivity S = [ergs s-1 cm-2] N = number of sources brighter than S Tuesday , November 9, 2010 simple example uniformly distributed source population all sources have same intrinsic luminosity for telescope sensitivity S, ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1011/vk_20101109.pdf -- 108.1 Кб -- 09.11.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/vk_20101109.pdf -- 108.1 Кб -- 09.11.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/vk_20101109.pdf -- 108.1 Кб -- 09.11.2010
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[ Текст ] Ссылки http://hea-www.harvard.edu/AstroStat/talks_1011/vk_20101109.pdf -- 108.1 Кб -- 09.11.2010
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/talks_1011/vk_20101109.pdf -- 108.1 Кб -- 09.11.2010
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111. AstroStat Talks 2011-2012
... 6 Sep 2011 . ... Biology appeared to lead astronomy in data analysis for many years, but the fields are now coming full circle. ... Slides [.pdf] . ... Simplicity: Bayesian Energy Quantiles, or Quick Non-parametric way(s) to incorporate Higher Dimensional Data (Alanna C) . ... In this talk I will discuss a hierarchical Bayesian approach to deriving the physical parameters of astronomical dust, as well as the distribution of these parameters. ... 1 Nov 2011 . ... slides [.pdf] . ... AcadYr 2011-2012 ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/ -- 30.7 Кб -- 02.02.2013
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/index.html -- 30.7 Кб -- 02.02.2013
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[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/index.html -- 30.7 Кб -- 02.02.2013
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112. http://hea-www.harvard.edu/AstroStat/Stat310_1112/2002ApJS..138..185F.pdf
THE ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 138 : 185 х 218, 2002 January ( 2002. The American Astronomical Society. All rights reserved. Printed in U.S.A. A WAVELET-BASED ALGORITHM FOR THE SPATIAL ANALYSIS OF POISSON DATA P. E. FREEMAN,1 V. KASHYAP,1 R. ROSNER,2 AND D. Q. LAMB2 Received 1999 April 9 ; accepted 2001 August 27 ABSTRACT Wavelets are scalable, oscillatory functions that deviate from zero only within a limited spatial regime and have average value zero, and thus may be used to simultaneously
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/2002ApJS..138..185F.pdf -- 940.2 Кб -- 07.02.2012
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/2002ApJS..138..185F.pdf -- 940.2 Кб -- 07.02.2012
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/2002ApJS..138..185F.pdf -- 940.2 Кб -- 07.02.2012
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113. http://hea-www.harvard.edu/AstroStat/Stat310_1112/ICASSP12_SDWH.pdf
POISSON NOISE REDUCTION WITH NON-LOCAL PCA J. Salmon C-A. Deledalle R. Willett Z. Harmany Duke University, ECE Department Durham, NC, USA CEREMADE, CNRS-Paris-Dauphine, Paris, France the data, a point of view also adopted in [13]. ... We apply patch based methods (also referred to as Non-Local methods) to Poisson noise, adapting PCA-based denoising in this heteroscedastic context. ... We coined our method Poisson NL-PCA, (for Non-Local Principal Component Analysi). ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/ICASSP12_SDWH.pdf -- 633.4 Кб -- 10.03.2012
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ICASSP12_SDWH.pdf -- 633.4 Кб -- 10.03.2012
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ICASSP12_SDWH.pdf -- 633.4 Кб -- 10.03.2012
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114. http://hea-www.harvard.edu/AstroStat/Stat310_1112/SchwartzmanJaffeGavrilovMeyer2011_MultipleTestingChIP-SeqPeaks.pdf
... Valid p-values for candidate peaks are computed via Monte Carlo simulations of smoothed Poisson sequences, whose background Poisson rates are obtained via linear regression from a Control sample and the local GC content. ... Other candidate p eaks, marked in blue, do not have a significantly higher binding rate in the IP sample than in the Control. ... Thus, as argued by SGA, it is enough to test for high binding rates only at locations that resemble p eaks, that is, local maxima of the smoothed...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/SchwartzmanJaffeGavrilovMeyer2011_MultipleTestingChIP-SeqPeaks.pdf -- 1152.8 Кб -- 07.02.2012
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/SchwartzmanJaffeGavrilovMeyer2011_MultipleTestingChIP-SeqPeaks.pdf -- 1152.8 Кб -- 07.02.2012
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/SchwartzmanJaffeGavrilovMeyer2011_MultipleTestingChIP-SeqPeaks.pdf -- 1152.8 Кб -- 07.02.2012
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115. http://hea-www.harvard.edu/AstroStat/Stat310_1112/ab_20110906.pdf
Taste of astrostatistics A taste of astrostatistics: problems, opportunities, & connections Alexander W Blocker 2011 Sep 06 Taste of astrostatistics Outline Outline 1 2 Astrostatistics in broad strokes Stacking: statistical challenges can come in small packages Problem Model Computation Data Results Lessons Event detection: massive, messy data Problem Method Results Lessons Connections 3 4 Taste of astrostatistics Astrostatistics in broad strokes What is astrostatistics? ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/ab_20110906.pdf -- 1327.9 Кб -- 06.09.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ab_20110906.pdf -- 1327.9 Кб -- 06.09.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ab_20110906.pdf -- 1327.9 Кб -- 06.09.2011
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116. http://hea-www.harvard.edu/AstroStat/Stat310_1112/ab_20120221.pdf
MIC Discussion Discussion of the Maximal Information Coefficient Alexander W Blocker http://www.awblocker.com/ Feb 21 2012 MIC Discussion Outline Outline 1 Defining MIC Subtleties technical issues Simon Tibshirani's response Broader concerns lessons 2 3 4 MIC Discussion Defining MIC Outline 1 Defining MIC Subtleties technical issues ... MIC Discussion Broader concerns & lessons Note Concerns here are not particular to the Reshef et al. paper. ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/ab_20120221.pdf -- 1209.1 Кб -- 21.02.2012
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ab_20120221.pdf -- 1209.1 Кб -- 21.02.2012
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/ab_20120221.pdf -- 1209.1 Кб -- 21.02.2012
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117. http://hea-www.harvard.edu/AstroStat/Stat310_1112/et_20111115.pdf
... Life arose very quickly on the early Earth. ... P[B|A] = probability of the data given the model = the likelihood (what we can obtain from a forward calculaCon) Pprior[A] = a priori probability the model is true/correct = the prior (oeen requires arbitrary judgment calls, source of controversy) P[B] = probability of the data (typically unknown, but only needed for normalizaCon) A Uniform Rate (Poisson) Model = rate of abiogenesis per Gyr per Earth like planet t = age of the ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/et_20111115.pdf -- 2466.2 Кб -- 15.11.2011
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/et_20111115.pdf -- 2466.2 Кб -- 15.11.2011
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/et_20111115.pdf -- 2466.2 Кб -- 15.11.2011
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118. http://hea-www.harvard.edu/AstroStat/Stat310_1112/jx_20120207.pdf
Outline Background Problem description Methodology Research New Results Two concerns New Results of Fully Bayesian JIN XU UCI February 7, 2012 JIN XU New Results of Fully Bayesian Outline Background Problem description Methodology Research New Results Two concerns Background Problem description Calibration Samples ... Our goal is to incorporate the uncertainty by Bayesian Methods. ... JIN XU New Results of Fully Bayesian ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1112/jx_20120207.pdf -- 1915.4 Кб -- 07.02.2012
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/jx_20120207.pdf -- 1915.4 Кб -- 07.02.2012
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1112/jx_20120207.pdf -- 1915.4 Кб -- 07.02.2012
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119. AstroStat Talks 2012-2013
... Presentations . ... Presentation Slides [.pdf] . ... In addition, systematic uncertainties in the characterization of the instruments have to be taken into account as they often can exceed the statistical uncertainties in the analysis of bright sources. ... This is a dry run for the SAMSI talk. ... Presentation slides [.pdf] . ... In this talk, I will first briefly review the problem and the Bayesian model, in which a zero-inflated gamma distribution is used to model the intensity of sources. ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1213/ -- 28.7 Кб -- 27.02.2014
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1213/index.html -- 28.7 Кб -- 27.02.2014
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1213/ -- 28.7 Кб -- 27.02.2014
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[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1213/index.html -- 28.7 Кб -- 27.02.2014
[ Сохраненная копия ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1213/ -- 28.7 Кб -- 27.02.2014
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120. http://hea-www.harvard.edu/AstroStat/Stat310_1213/PDB_LogNLogS_051013.pdf
Bayesian Estimation of log N - log S Paul D. Baines Department of Statistics University of California, Davis May 10th, 2013 Introduction Project Goals Develop a comprehensive method to infer (properties of ) the distribution of source fluxes for a wide variety source populations. ... Collect raw data images 2. ... Probabilistic Connection: Under independent sampling, linearity on the log N - log S scale is equivalent to the flux distribution being a Pareto distribution. ...
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Ссылки http://hea-www.harvard.edu/AstroStat/Stat310_1213/PDB_LogNLogS_051013.pdf -- 1127.6 Кб -- 10.05.2013
[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1213/PDB_LogNLogS_051013.pdf -- 1127.6 Кб -- 10.05.2013
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[ Текст ] Ссылки http://hea-www.harvard.edu/astrostat/Stat310_1213/PDB_LogNLogS_051013.pdf -- 1127.6 Кб -- 10.05.2013
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