ST733: Lectures & Assignments

ST733 Applied Spatial Statistics Spring Session, 2005 Expect frequent changes
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	Date		Lecture coverage	Homework assignments
1	Jan 11	Tu	Basic concepts: Why Spatial Statistics?	No HW	Read Chapter 1 from optional text
2	Jan 13	Th	Autocorrelation functions: Lecture Notes I	HW1	Read Lecture Notes I, p.4-10. HW1 due on 01/20/2005
3	Jan 18	Tu	Discussions on HW1, Cross-correlations	no HW	Read Lecture Notes I, p.11-14.
4	Jan 20	Th	Testing for Autocorrelations	HW2	Read Lecture Notes I, p.15-21. HW2 due on 02/01/05
5	Jan 25	Tu	Join Counts (BW & BB) Lab1: Introduction to R	no HW	Read Lecture Notes I, p.22-27. Read the R manual, Sec.1.4, Chap.s 2, 5, 7 13 and Appendix A
6	Jan 27	Th	Moran's I and Geary's c	no HW	Read Lecture Notes I, p.29-35
7	Feb 1	Tu	Semi-variograms: Lecture Notes II Lab2: Computing test statistics	HW2 due	Read Lecture Notes II, p.1-6. Writing R function: mycode.R Computing test statistics using sts.R function
8	Feb 3	Th	Modeling sample semivariograms R codes used in class	HW3	Read Lecture Notes II, p.7-18. Data sets: soilph and ozone
9	Feb 8	Tu	Fitting variogram models Lab3: Computing sample variograms	No HW	Read Lecture Notes II, p.12-18. Data set rain (source: UCLA Statistics)
10	Feb 10	Th	Confidence Intervals for variograms	no HW	Read Lecture Notes II, p.19-23
11	Feb 15	Tu	Models for anisotrpic semivariograms Lab4: Introduction to geoR	HW3 due	Read Lecture Notes II, p.24-36, A introduction to geoR The geoR manual Solution to HW3: hw3_1.R and hw3_2.R
12	Feb 17	Th	Prediction: Lecture Notes III	HW4	Read Lecture Notes III, p.1-6.
13	Feb 22	Tu	Simple and Ordinary Kriging	no HW	Read Lecture Notes III, p.7-11.
14	Feb 24	Th	Effect of variograms on predictions	HW4 due	Read Lecture Notes III, p.12-21. Solution to HW4: hw4.R
15	Mar 1	Tu	Kriging us BLUP Lab5: Spatial predictions	no HW	Read Lecture Notes III, p.22-34. Use rain data for Lab5
16	Mar 3	Th	Solve Practice problems I	no HW	Practice Problems -I
17	Mar 8	Tu	Spring Break	no HW	No classes
18	Mar 10	Th	Spring Break	no HW	No Classes
19	Mar 15	Tu	Midterm Exam 2:35 to 3:30, 3216 Broughton Hall	Midterm	Syllabus: Lectures 1-14
20	Mar 17	Th	Universal Kriging: Lecture Notes IV	HW5	Read Lecture Notes IV, p.1-13
21	Mar 22	Tu	Regression with Spatially Correlated Errors Lab6	no HW	Read Lecture Notes IV, p.14-22. Use extended rain data for Lab6
22	Mar 24	Th	Spring Holiday		No classes
23	Mar 29	Tu	ML estimation Lab7	HW5 due	Read Lecture Notes IV, p.23-34. Use extended rain data for Lab7 Solution to HW5: hw5.R and hw5soln.txt
24	Mar 31	Th	REML	HW6	Read Lecture Notes IV, p.35-36 Data for HW6: simdata
25	Apr 5	Tu	Block kriging	no HW	Read Lecture Notes IV p.38-41, No lab today!
26	Apr 7	Th	Cokriging	HW6 due	Read Lecture Notes IV, p.42-51. Solution hw6.R
27	Apr 12	Tu	More covariance structures Case Study I: Kriging Gas price (presented by Tom Colson)	HW 7	Read Lecture Notes IV, p.55-59. No Lab today! Data for case study I: data1
28	Apr 14	Th	Computing block kriging	no HW	Compute block kriging using krige.block.R
29	Apr 19	Tu	Case study II: Kriging traffic counts (presented by JinKi Eom) Lab8: explaining krige.block	HW 8 HW7 due	Data for case study II:data2 Data for HW8: simdatau.txt and simdatav.txt Solution to HW7: hw7.R and hw7soln.txt
30	Apr 21	Th	Case study III: kriging visit days (presented by Jessica Robinson)	no HW	Data for case study III: data3 and the R history
31	Apr 26	Tu	Problem solving session	HW8 due	Practice problems set II Solution to HW8: hw8.R and hw8soln.txt
32	Apr 28	Th	Problem solving session	no HW	Discussions and feedback Solution to PP2: pp2soln.R and pp2soln.txt
	May 3	Tu	Take home Final exam Completed Exam should be turned in to the instructor by May 3rd 4:00PM (sharp! no extension)	Final	Syllabus: Lectures 1-30. Exam will be posted on May 2nd 9:00AM Turn in the hard copies of completed exam at 203A Patterson Hall (no e-mail submission is allowed)