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UID:6827ae3063a25
DTSTART;TZID=America/Toronto:20170511T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20170511T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-professor-peter-diggle
SUMMARY:David Sprott Distinguished Lecture by Professor Peter Diggle\,\nLan
 caster University
CLASS:PUBLIC
DESCRIPTION:Summary \n\nA TALE OF TWO PARASITES: HOW CAN GAUSSIAN PROCESSES
  CONTRIBUTE TO\nIMPROVED PUBLIC HEALTH IN AFRICA?\n\nIn this talk\, I will
  rst make some general comments about the role of\nstatistical modelling i
 n scientic research\, illustrated by two\nexamples from infectious disease
  epidemiology. I will then describe in\ndetail how statistical modelling b
 ased on Gaussian spatial stochastic\nprocesses has been used to construct 
 region-wide risk maps to inform\nthe operation of a multi-national control
  programme for onchocerciasis\n(river blindness) in equatorial Africa. Fin
 ally\, I will describe\nwork-in progress aimed at exploiting recent develo
 pments in mobile\nmicroscopy to enable more precise local predictions of c
 ommunity-level\nrisk.\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae30649ac
DTSTART;TZID=America/Toronto:20161020T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20161020T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-professor-david-donoho
SUMMARY:David Sprott Distinguished Lecture by Professor David Donoho\, Stan
 ford\nUniversity 
CLASS:PUBLIC
DESCRIPTION:Summary \n\nFACTOR MODELS AND PCA IN LIGHT OF THE SPIKED COVAR
 IANCE MODEL\n\n[DAVID L. DONOHO DAVID SPROTT DISTINGUISHED LECTURE BY DAVI
 D L. DONOHO\nFactor Models and PCA in light of the spiked covariance model
 \nThursday\, October 20\, 2016 | 4 p.m.]\n[/statistics-and-a
 ctuarial-science/sites/ca.statistics-and-actuarial-science/files/uploads/f
 iles/distinguished_lecture_poster-donoho-pr4.pdf]\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae3065fa6
DTSTART;TZID=America/Toronto:20160512T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20160512T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-martin-wainwright
SUMMARY:David Sprott Distinguished Lecture by Martin Wainwright\, Universit
 y of\nCalifornia\, Berkeley
CLASS:PUBLIC
DESCRIPTION:Summary \n\nSOME NEW PHENOMENA IN HIGH-DIMENSIONAL STATISTICS A
 ND OPTIMIZATION\n\nStatistical models in which the ambient dimension is of
  the same order\nor larger than the sample size arise frequently in differ
 ent areas of\nscience and engineering.  Examples include sparse regressio
 n in\ngenomics\; graph selection in social network analysis\; and low-rank
 \nmatrix estimation in video segmentation.  Although high-dimensional\nmo
 dels of this type date back to seminal work of Kolmogorov and\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae30667a6
DTSTART;TZID=America/Toronto:20150924T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20150924T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-raymond-j-carroll-texas
SUMMARY:David Sprott distinguished lecture by Raymond J. Carroll\, Texas A&
 M\nUniversity
CLASS:PUBLIC
DESCRIPTION:Summary \n\nCONSTRAINED MAXIMUM LIKELIHOOD ESTIMATION FOR MODEL
  CALIBRATION USING\nSUMMARY-LEVEL INFORMATION FROM EXTERNAL BIG DATA SOURC
 ES.\n\n[Carroll Poster]\n[/statistics-and-actuarial-sc
 ience/sites/ca.statistics-and-actuarial-science/files/uploads/files/pdf.po
 ster-carroll_1.pdf]Information\nfrom various public and private data sourc
 es of extremely large sample\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae3067159
DTSTART;TZID=America/Toronto:20130913T143000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20130913T143000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-jerome-friedman
SUMMARY:David Sprott Distinguished Lecture by Jerome Friedman
CLASS:PUBLIC
DESCRIPTION:Summary \n\nSPARSITY\, BOOSTING AND ENSEMBLE METHODS\n\n[Jerome
  Friedman]Statistical or machine learning involves predicting\nfuture outc
 omes from past observations. Many present day applications\ninvolve large
  numbers of predictor variables\, sometimes much larger\nthan the number 
 of cases or observations available to train the\nlearning algorithm. In s
 uch situations traditional statistical\nmethods fail.\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae30678f0
DTSTART;TZID=America/Toronto:20130110T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20130110T160000
URL:/statistics-and-actuarial-science/events/first-annu
 al-distinguished-lecture-david-spiegelhalter
SUMMARY:First annual distinguished lecture by David Spiegelhalter
CLASS:PUBLIC
DESCRIPTION:Summary \n\nDON'T KNOW\, CAN'T KNOW: COMMUNICATING RISK AND DEE
 PER UNCERTAINTY\n\nDavid Spiegelhalter\, Winton Professor of the Public Un
 derstanding of\nRisk\, University of Cambridge\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae3067ede
DTSTART;TZID=America/Toronto:20140925T143000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20140925T143000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-eduardo-s-schwartz
SUMMARY:David Sprott Distinguished Lecture by Eduardo S. Schwartz
CLASS:PUBLIC
DESCRIPTION:Summary \n\nTHE REAL OPTIONS APPROACH TO VALUATION: CHALLENGES 
 AND OPPORTUNITIES\n\n[Eduardo Schwartz]This lecture provides an overview o
 f the real\noptions approach to valuation mainly from the point of view of
  the\nauthor who has worked in this area for over 30 years. After a genera
 l\nintroduction to the subject\, numerical procedures to value real\noptio
 ns are discussed.\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae306846f
DTSTART;TZID=America/Toronto:20140514T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20140514T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-art-b-owen
SUMMARY:David Sprott Distinguished Lecture by Art B. Owen
CLASS:PUBLIC
DESCRIPTION:Summary \n\nEMPIRICAL LIKELIHOOD\n\n[Art Owen]Likelihood method
 s provide one of the most versatile and\neffective ways to handle data. Th
 ey give us tests and confidence\nintervals with very strong optimality mea
 sures. But the cost for using\nthem is usually that we have to know a fami
 ly of distributions\ngenerating our data.\n 
DTSTAMP:20250516T212920Z
END:VEVENT
BEGIN:VEVENT
UID:6827ae3068a74
DTSTART;TZID=America/Toronto:20150514T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20150514T160000
URL:/statistics-and-actuarial-science/events/david-spro
 tt-distinguished-lecture-bill-woodall
SUMMARY:David Sprott distinguished lecture by William Woodall\, Virginia Te
 ch
CLASS:PUBLIC
DESCRIPTION:Summary \n\nMONITORING AND IMPROVING SURGICAL QUALITY\n\nSome s
 tatistical issues related to the monitoring of surgical quality\nwill be r
 eviewed in this presentation. The important role of\nrisk-adjustment in he
 althcare\, used to account for variations in the\ncondition of patients\, 
 will be described. Some of the methods for\nmonitoring quality over time\,
  including a new one\, will be outlined\nand illustrated with examples.\n 
DTSTAMP:20250516T212920Z
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