# Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.

58 Pages

### Extreme Value Distributions AMS2009

Course: GEO 6938, Summer 2011
School: University of Florida
Rating:

Word Count: 2074

#### Document Preview

VALUE EXTREME THEORY Richard L. Smith Department of Statistics and Operations Research University of North Carolina Chapel Hill, NC 27599-3260 rls@email.unc.edu AMS Committee on Probability and Statistics Short Course on Statistics of Extreme Events Phoenix, January 11, 2009 1 (From a presentation by Myles Allen) 2 3 4 OUTLINE OF TALK I. Extreme value theory Probability Models Estimation Diagnostics II....

Register Now

#### Unformatted Document Excerpt

Coursehero >> Florida >> University of Florida >> GEO 6938

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

University of Florida - GEO - 6938
An Application of Extreme Value Theory for Measuring RiskManfred Gilli, Evis Kllezi eDepartment of Econometrics, University of Geneva and FAME CH1211 Geneva 4, SwitzerlandAbstract Many fields of modern science and engineering have to deal with events w
University of Florida - GEO - 6938
1WHY EXTREME VALUE THEORY?1.1 A Simple Extreme Value ProblemMany statistical tools are available in order to draw information concerning specific measures in a statistical distribution. In this textbook, we focus on the behaviour of the extreme values
University of Florida - GEO - 6938
Spatial analysis of density dependent pattern in coniferous forest stands*Janet Franklin 1, Joel Michaelsen 1 &amp; Alan H. Strahler2*, *1Department of Geography, University of California, Santa Barbara, California, 93106; 2Department of Geology and Geograp
University of Florida - GEO - 6938
Generalized extreme value distribution - Wikipedia.http:/en.wikipedia.org/wiki/Extreme_value_distri.Your continued donations keep Wikipedia running!Generalized extreme value distributionFrom Wikipedia, the free encyclopedia(Redirected from Extreme va
University of Florida - GEO - 6938
GeoDa: An Introduction to Spatial Data AnalysisLuc Anselin, Ibnu Syabri and Youngihn Kho Spatial Analysis Laboratory Department of Agricultural and Consumer Economics University of Illinois, Urbana-Champaign Urbana, IL 61801 USAanselin@uiuc.edu, syabri@
University of Florida - GEO - 6938
Geographical Analysis ISSN 0016-7363GeoDa: An Introduction to Spatial Data AnalysisLuc Anselin1, Ibnu Syabri2, Youngihn Kho11Spatial Analysis Laboratory, Department of Geography, University of Illinois, Urbana, IL, 2Laboratory for Spatial Computing an
University of Florida - GEO - 6938
Exploring Spatial Data with GeoDaTM : A WorkbookLuc AnselinSpatial Analysis Laboratory Department of Geography University of Illinois, Urbana-Champaign Urbana, IL 61801http:/sal.agecon.uiuc.edu/Center for Spatially Integrated Social Sciencehttp:/www.
University of Florida - GEO - 6938
Available online at www.sciencedirect.comEconomics Letters 99 (2008) 585 590 www.elsevier.com/locate/econbaseFunctional forms for the negative binomial model for count dataWilliam Greene Department of Economics, Stern School of Business, New York Univ
University of Florida - GEO - 6938
Geographical Processes and the Analysis of Point Patterns: Testing Models of Diffusion by Quadrat Sampling Author(s): D. W. Harvey Source: Transactions of the Institute of British Geographers, No. 40 (Dec., 1966), pp. 81-95 Published by: Blackwell Publish
University of Florida - GEO - 6938
Some Methodological Problems in the Use of the Neyman Type A and the Negative Binomial Probability Distributions for the Analysis of Spatial Point Patterns Author(s): David Harvey Source: Transactions of the Institute of British Geographers, No. 44 (May,
University of Florida - GEO - 6938
Landscape Ecology 15: 467478, 2000. 2000 Kluwer Academic Publishers. Printed in the Netherlands.467Lacunarity analysis of spatial pattern: A comparisonM.R.T. DaleDepartment of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Can
University of Florida - GEO - 6938
GEO 6938 Advanced Quantitative Methods for Spatial Analysis Spring 2012 Timothy J. Fik, Ph.D. Associate Professor Department of Geography University of Florida e-mail: &quot;fik@ufl.edu&quot;Selected Topics include. Point-Pattern/Pattern Analysis &amp; Modeling Cluste
University of Florida - GEO - 6938
Lab #1. Point Pattern Analysis using Quadrat counts Carry out a point pattern analysis using quadrat counts based on grid cells superimposed on a given study (a two dimensional surface) containing a spatial distribution of points that represent the locati
University of Florida - GEO - 6938
Poisson Regression. continuedIn the PR model, the mean and variance V are assumed/restricted to be equal.something that rarely occurs in practice (as real data almost always rejects this restriction when tested).Typically, the variance is greater than t
University of Florida - GEO - 6938
Spatial Diffusion &amp; Pattern AnalysisFive general types of spatial diffusion processes.3 2 11. Expansion Diffusion a simple outward expansion from the source (covering a larger, more extensive area over time).Study area2. Relocation Diffusion the move
University of Florida - GEO - 6938
Nearest-Neighbor MethodsDefining &quot;connectivity&quot; between points Point data can be used in various ways to measure the degree to which the point pattern exhibits spatial autocorrelation.But first, care must be taken in describing the nature of connectivit
University of Florida - GEO - 6938
Analysis of Pattern Measuresat the Local/Regional Scale9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.Local Moran's I The Score Statistic Also Getis G-statistic Tango's CF (which we will review later) 2 Cumulative test Maximum 2 test Local Quadrat Test
University of Florida - GEO - 6938
Identification of Local Clusters for Count Data: A Model-Based Moran's I TestTonglin Zhang and Ge LinPurdue University and West Virginia University February 14, 2007Department of Statistics, Purdue University, 250 North University Street,West Lafayette
University of Florida - GEO - 6938
Chapter 4 Modelling Counts - The Poisson and Negative Binomial RegressionIn this chapter, we discuss methods that model counts. In a longitudinal setting, these counts typically result from the collapsing repeated binary events on subjects measured over
University of Florida - GEO - 6938
Notes on the Negative Binomial DistributionJohn D. Cook October 28, 2009Abstract These notes give several properties of the negative binomial distribution. 1. Parameterizations 2. The connection between the negative binomial distribution and the binomia
University of Florida - GEO - 6938
On Model Fitting Procedures for Inhomogeneous Neyman-Scott ProcessesYongtao GuanJuly 31, 2006ABSTRACTIn this paper we study computationally efficient procedures to estimate the second-order parameters for a class of inhomogeneous Neyman-Scott processe
University of Florida - GEO - 6938
Spatial AutocorrelationGeography 683 - Introduction to Geographic AnalysisSpatial AutocorrelationGuoxiang Ding Department of Geography1155 Derby Hall Phone: 292-2704 Email: ding.45@osu.edu First law of geography: &quot;everything is related to everything
University of Florida - GEO - 6938
Overdispersion and Poisson RegressionRichard Berk John MacDonald Department of Statistics Department of Criminology University of Pennsylvania November 19, 2007Abstract This article discusses the use of regression models for count data. A claim is often
University of Florida - GEO - 6938
Spatial AutocorrelationMoran's I Geary's C Arthur J. Lembo, Jr. Salisbury UniversitySpatial Autocorrelation First law of geography: &quot;everything is related to everything else, but near things are more related than distant things&quot; Waldo Tobler Many geog
University of Florida - GEO - 6938
Analysing spatial point patterns in RAdrian Baddeley CSIRO and University of Western Australia Adrian.Baddeley@csiro.au adrian@maths.uwa.edu.au Workshop Notes Version 3 October 2008 Copyright c CSIRO 2008Abstract This is a detailed set of notes for a wo
University of Florida - GEO - 6938
136Poisson Regression Analysis13. Poisson Regression AnalysisWe have so far considered situations where the outcome variable is numeric and Normally distributed, or binary. In clinical work one often encounters situations where the outcome variable is
University of Florida - GEO - 6938
Parametric Test Quadrat AnalysisEquations taken from Rogerson, 2001.i=m i =1s2 = (xs2 xi- x )2m -1 m -1 (VMR - 1) z= 2 m is the number of quadrats, x is the mean of the number of points per quadrat, s2 is the variance of the number of points per
University of Florida - GEO - 6938
AN INTRODUCTION TO QUADRAT ANALYSISR.W.ThomasISSN 0306-6142ISBN 0 902246 66 6 1977 R.W. ThomasCONCEPTS AND TECHNIQUES IN MODERN GEOGRAPHY No. 12CATMOG(Concepts and Techniques in Modern Geography) CATMOG has been created to fill a teaching need in th
University of Florida - GEO - 6938
Rate Transformations and SmoothingLuc Anselin Nancy Lozano Julia KoschinskySpatial Analysis Laboratory Department of Geography University of Illinois, Urbana-Champaign Urbana, IL 61801 http:/sal.uiuc.edu/Revised Version, January 31, 2006Copyright c 20
University of Florida - GEO - 6938
Change Detection Thresholds: Alternative Statistical Approaches to Detecting Temporal Change in Spatial PatternsPeter A. Rogerson Daikwon Han Ikuho Yamada Department of Geography National Center for Geographic Information and Analysis University at Buffa
University of Florida - GEO - 6938
The author(s) shown below used Federal funds provided by the U.S. Department of Justice and prepared the following final report: Document Title: Author(s): Document No.: Date Received: Award Number: Crime Analysis Geographic Information System Services: A
University of Florida - GEO - 6938
Spatial AutocorrelationMorans I Gearys C Arthur J. Lembo, Jr. Salisbury UniversitySpatial Autocorrelation First law of geography: everything is related to everything else, but near things are more related than distant things Waldo Tobler Many geograph
University of Florida - GEO - 6938
SaTScan User GuideTMfor version 8.0By Martin Kulldorff February, 2009 http:/www.satscan.org/ContentsIntroduction . 4 The SaTScan Software . 4 Download and Installation . 5 Test Run . 5 Sample Data Sets. 5 Statistical Methodology.
University of Florida - GEO - 6938
Further Methods for Point Pattern AnalysisBailey and Gatrell Chapter 4Variations in Populationn Certain types of events will exhibit clustering due to heterogeneity in the underlying distribution e.g disease cases or crimes will tend to cluster where t
University of Florida - GEO - 6938
Non-technical Overview of Geospatial Statistical MethodsGIS/Mapping and Census Data Second Annual Census Workshop Series Workshop 3: Spatial Statistics, Spatial Research &amp; Confidential Census DataNew York Census Research Data Center (CRDC) Baruch Colleg
University of Florida - GEO - 6938
Package `spatstat'December 21, 2011Version 1.25-1 Date 2011-12-21 Title Spatial Point Pattern analysis, model-fitting, simulation, tests Author Adrian Baddeley &lt;Adrian.Baddeley@csiro.au&gt; and Rolf Turner &lt;r.turner@auckland.ac.nz&gt; with substantial contrib
University of Florida - GEO - 6938
Andrei Rogers and Norbert G. GomarStatistical inference in Quadrat AnalysisThe growing recognition of the need for establishing a systematic and quantitative means for describing and analyzing, the spatial dispersion of activities in urban areas has gen
University of Florida - GEO - 6938
Biometrical Journal 50 (2008) 1, 4357 DOI: 10.1002/bimj.20061033943Parameter Estimation and Model Selection for Neyman-Scott Point ProcessesUshio Tanaka1, Yosihiko Ogata*, 1, 2, and Dietrich Stoyan31 2 3The Graduate University for Advanced Studies, M
University of Florida - GEO - 4167
Review of Matrix AlgebraMatrices A matrix is a rectangular or square array of values arranged in rows and columns. An m n matrix A, has m rows and n columns, and has a general form of a11 a = 21 . am1 a12 a22 . am 2 . a1n . a2 n . . . amn mn mn1Exa
University of Florida - GEO - 4167
University of Florida - GEO - 4167
Geographically Weighted RegressionA Tutorial on using GWR in ArcGIS 9.3Martin Charlton A Stewart FotheringhamNational Centre for Geocomputation National University of Ireland Maynooth Maynooth, County Kildare, Ireland http:/ncg.nuim.ieThe authors grat
University of Florida - GEO - 4167
GEOGRAPHICALLY WEIGHTED REGRESSIONWHITE PAPERMARTIN CHARLTON A STEWART FOTHERINGHAMNational Centre for Geocomputation National University of Ireland Maynooth Maynooth, Co Kildare, IRELANDMarch 3 2009The authors gratefully acknowledge support from a S
University of Florida - GEO - 4167
Lab#1, Spring 2012 (25 points) GEO 4167/GEO 6161 Intermediate Quantitative Methods (Fik) Name: _ Score: _ Instructions: Complete this lab to the best of your abilities. Attach your work sheets, relevant computer output, results, and write-up to this cover
University of Florida - GEO - 4167
Polynomial regressionDaniel Borcard, Dpartement de sciences biologiques, Universit de Montral Reference: Legendre and Legendre (1998) p. 526A variant form of multiple regression can be used to fit a nonlinear model of an explanatory variable x (or sever
University of Florida - GEO - 4167
Board of the Foundation of the Scandinavian Journal of Statistics 2004. Published by Blackwell Publishing Ltd, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA Vol 31: 515534, 2004Functional Coefficient Regression Mode
University of Florida - GEO - 4167
AN INTRODUCTION TO TREND SURFACE ANALYSISD.UnwinISSN 0305-6142 ISBN 0 902246 51 8 1978 David J. UnwinCONCEPTS AND TECHNIQUES IN MODERN GEOGRAPHY No. 5CATMOG(Concepts and Techniques in Modern Geography) CATMOG has been created to fill a teaching need
University of Florida - GEO - 4167
Intermediate Quantitative MethodsTimothy J. Fik Associate Professor GEO 4167 section #6647 (undergraduate) GEO 6161 section #8377 (graduate)Credit hours: 3Thursdays (periods 2-4): 8:30-11:30AM Location: TUR 3012 SPRING 2012Intermediate Quantitative Me
University of Florida - GEO - 4167
More on the Reliability, Precision, and Performance of the regression model and its estimated parameters. As the least-squares coefficient/parameter estimates ( j's) and the SRF's ability to explain variation in the dependent variable (Y) can vary from sa
University of Florida - GEO - 4167
II. Testing for Multicollinearity When two or more independent variables in a regression model are highly correlated with one another (or collinear), they will contribute &quot;redundant&quot; explanatory information. Hence, not all of those independent variables
University of Florida - GEO - 4167
Recall our recent Reading Assignments. Read and review: (a) the technical appendix in your textbook on Matrix approach to LS regression. Basic Econometrics by D. Gujarati, 2007, 4th edition. and/or (b) the posted Matrix Algebra review and the Matrix Appro
University of Florida - GEO - 4167
Extending Linear Regression: Weighted Least Squares, Heteroskedasticity, Local Polynomial Regression36-350, Data Mining 23 October 2009Contents1 Weighted Least Squares 2 Heteroskedasticity 2.1 Weighted Least Squares as a Solution to Heteroskedasticity
University of Florida - GEO - 4167
OLS Under Heteroskedasticity Testing for HeteroskedasticityHeteroskedasticity and Weighted Least SquaresWalter Sosa-EscuderoEcon 507. Econometric Analysis. Spring 2009April 14, 2009Walter Sosa-EscuderoHeteroskedasticity and Weighted Least SquaresOL
University of Florida - GEO - 4167
Regression Analysis Tutorial183LECTURE / DISCUSSION Weighted Least SquaresEconometrics Laboratory C University of California at Berkeley C 22-26 March 1999Regression Analysis Tutorial184IntroductionIn a regression problem with time series data (whe
University of Florida - GEO - 4167
Intermediate Quantitative MethodsTimothy J. Fik Associate Professor GEO 4167 section #6647 (undergraduate) GEO 6161 section #8377 (graduate)Credit hours: 3Thursdays (periods 2-4): 8:30-11:30AM Location: TUR 3012 SPRING 2012Intermediate Quantitative Me
University of Florida - AST - 1002
UFIDQ1 9.2 8.25 4.5 8 9.85 5.5 9.1 10 7.5 4.5 9.85 6 3.5 7 6.35 10 9 7.5 9.5 5.25 6.75 5 5.75 2.5 5.25 3.25 6.1 7 6.5 9.1 5 3.25 6.5 8.75 9 3.5 10 5 4.1 5.1 4.5 6.7501713653 03291993 03891805 05193165 09669612 11156163 11161338 11314038 11334031 1139879
University of Florida - AST - 1002
1/19/12discoveredinNov2011~600lyfromEarth P=290daysThe1stexoplanetorbiAngwithintheGoldilockzonearoundaSunlikestarReviewonLecture2WhyPtolemy'sEpicycleModelwasagoodtheory? WhyPtolemy'sEpicycleModelwasnotagood theory? Inwhataspect,Kepler'sModelissuperio
University of Florida - AST - 1002
1/19/12ImportantNo/ce1stQuizonJan26(1weekfromtoday) about10~15problems mul/plechoice+T,F+answering +simplemath? itwillcoverChap0.2. Tipsforstudyingthetextbook.Exoplanets51Pegasib*1stexoplanetdiscovered (1995)orbi/ngaSunlikestar CentralStar(51Pegasi)
University of Florida - AST - 1002
1/24/12Observa-onProjectI:Observingthe FullCycleoftheMoonAim:Understandingtherela-vemo-ons betweentheMoon&amp;Sunbyobserving 1)theloca-onoftheMoonintheskyata fixedobserva-on-me 2)thephaseoftheMoon Due:1weekbeforetheFinalExamObserva-onProjectI:Observingthe
University of Florida - AST - 1002
1/27/12ReviewL02L051.BeginningoftheModernAstronomy Aristotle,Ptolemy,Copernicus,Kepler,Newton 2.Exoplanets(examples&amp;generalproperMes) mass,eccentricity,distancefromhoststars,numberofmembers &amp;layout 3.DetecMonMethodsofExoplanets directimagingwithAO radia
University of Florida - AST - 1002
What'supUniverse? TheStrongestSolarFlareIn2012,arewedoomed?UnderstandingOurWorld,SolarSystemChap48kpclyrSolarSystemLayout(1)30AU 100AU 105AULaunchedin1977 V=20,000m/sAsofAug2006OortCloudisahypothePcalshellwhichiscomposedofnumerous cometlikebodie
University of Florida - AST - 1002
EarthMoonSystemPlanetEarthP=365days d=1AU =5,500kg/m3 6,387kmMoon=3,300kg/m3 1,738kmChap5StudyingEarth:LandscapesStudyingEarth:OverallStructure6mainlayersofEarth1)MetallicCores(ironcore) 2)Mantle(Silicatemantle) 3)Crust 4)Atmosphere 5)Trophospher