STAT 544 - APPLIED SPATIAL STATISTICS


Instructor

  • Jon Graham

  • Syllabus

  • Course Syllabus

  • Lecture 1&2 Videorecordings

  • Video Lecture (Thursday, 4/26): Quadrat and Distance Methods
  • Homework Assignments

    Assignment Solutions R Code Due Date Papers
    Homework #1 HW#1 Solutions HW#1 Code Friday, February 10
    Homework #2 HW#2 Solutions HW#2 Code Monday, February 27
    Homework #3 HW#3 Solutions HW#3 Code Monday, March 12 Maravelias, et al. paper
    Homework #4 HW#4 Solutions HW#4 Code Wednesday, March 28
    Homework #5 HW#5 Solutions HW#5 Code Wednesday, April 25
    Homework #6 Friday, May 11 Legendre paper

    Data Sets

    Name Description
    phytoph.txt Phytophthora Disease/Moisture Data
    longleaf.txt Longleaf pine data from Thomas County, GA (p. 16 of notes)
    swiss.txt Switzerland Rainfall Data
    woodpecker.txt Woodpecker Count Data
    walk100.txt Walker Lake Illustrative Data (n=100)
    walk470.txt Walker Lake Sample Data (n=470)
    landsateng.txt England LANDSAT Data
    vgreen.txt Visual Greenness Data
    grav110.txt Gravity Data
    ironore.txt Iron Ore Data
    arsenic.txt Arsenic Concentration Data
    scallops.txt Scallops Data
    ireland.txt Ireland County Data
    air.txt Europe Air Emissions Data
    carex.txt Presence/Absence Carex Data

    R Functions

    Function Description
    allfunctions.r Collection of all functions below
    image.legend.r Puts a legend on an image (greyscale) plot
    ppnorm.r Creates a normal probability plot
    movewin.r Calculates moving windows statistics (for any type of data)
    hscatter.r Produces h-Scatterplots and computes C(h),p(h),gamma(h)
    corrplot.r Plots C(h),p(h),gamma(h)
    triangfuncs Triangulation functions for use with "polydec.r" function
    polydec Performs polygonal declustering on a set of spatial data
    celldec Performs cell declustering on a set of spatial data
    point.crossval Performs crossvalidation for the point estimation methods
    rose.r Produces a rose plot from variogram output
    rotateaxis.r Rotates coordinates a prescribed angle clockwise from 0 degrees north
    panel.gamma0.r Panel function for plotting directional variograms with ranges shown
    getCD Computes the C and D covariance matrices for kriging
    ordkrige Performs ordinary kriging given data and variogram parameters
    ok.crossval Performs crossvalidation of ordinary kriging predictions & other methods
    clarkevans Conducts the Clark-Evans Test of CSR

    Course Handouts

    Reading Title R Scripts
    N/A Introduction to R N/A
    Chapter 1, Section 1 (Schabenberger & Gotway)
    Chapter 1 (Bailey & Gatrell)
    Introduction to Spatial Statistics intro.r
    Chapters 2-4 (Isaaks & Srivastava) Walker Lake Data - An Exploratory Description walker.r
    Chapter 5 (Bailey & Gatrell) Covariograms, Correlograms, Variograms variog.r
    Chapter 6 (Bailey & Gatrell) Cross-Covariograms, Correlograms, Variograms crossvar.r
    Chapters 5-6 (Isaaks & Srivastava) Notes on Walker Lake Data Sets walker2.r
    Chapter 5.4.1,5.4.2 (Bailey & Gatrell) Global and Point Estimation estimate.r
    Chapters 10-11 (Isaaks \& Srivastava) Estimation Criteria estim2.r
    Chapter 5.4.4 (Bailey & Gatrell)
    Chapter 7 (Isaaks & Srivastava)
    Empirical Semivariograms empvariog.r
    Chapter 5.4.4 (Bailey & Gatrell) Alternatives to the Classical Variogram Estimator varalter.r
    Chapter 7.4 (Bailey \& Gatrell) Parametric/Median Polish Trend Removal medpol.r
    Chapter 5.5.3 (Bailey & Gatrell) Theoretical Semivariogram Models varmodel.r
    Chapter 5.5.3 (Bailey & Gatrell) Fitting Variogram Models variofit.r
    Chapter 5.5.3 (Bailey & Gatrell) Correcting for & Fitting Variograms with Anisotropies anisofit.r
    Chapter 5.5.5 (Bailey & Gatrell)
    Chapter 12 (Isaaks & Srivastava)
    Ordinary Kriging ordkrige.r
    Chapter 5.5.5 (Bailey & Gatrell)
    Chapter 12 (Isaaks & Srivastava)
    Effect of the Variogram Function on Kriging
    N/A Crossvalidation
    N/A Modeling Trend and Variation
    N/A Universal Kriging ukrige.r
    N/A Cokriging
    Review Sheet - Midterm
    Chapter 7.4,7.5 (Bailey & Gatrell) Moran's I and Geary's C Statistics moran.r
    Chapter 7.4.1 (Bailey & Gatrell) Spatial Lattice Data and Neighborhoods
    Chapter 7.5.4 (Bailey & Gatrell) More on Spatial Lattice Models lattmod.r
    An Autologistic Model Example autolog.r
    Chapter 3.1-3.5 (Bailey & Gatrell)
    Chapter 3 (Schabenberger & Gotway)
    Spatial Point Pattern Analysis pointpat.r
    Chapter 3.1-3.5 (Bailey & Gatrell)
    Chapter 3 (Schabenberger & Gotway)
    Distance Methods distance.r
    Chapter 3.4.4 (Bailey & Gatrell) Ripley's K Function ripley.r

    The 6th homework was assigned on Wednesday, April 25 and is due on Friday, May 11.

    Last modified: 2-May-2012
    Mail comments to: jgraham@mso.umt.edu