MRT10 Resampling techniques and Statistical Modelling

Faculty of Science
Autumn 2007
Extent and Intensity
0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: z (credit).
Teacher(s)
Prof. Lola Ugarte (lecturer), prof. RNDr. Ivanka Horová, CSc. (deputy)
Guaranteed by
prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science
Contact Person: prof. RNDr. Ivanka Horová, CSc.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Resampling techniques with R Environmental Case Studies 1.- Small area estimation using linear models: estimation of the number of hectares occupied byfruit trees in Navarra, Spain 2.- Spatial Statistics for Environmental Epidemiology: disease mapping using an Empirical Bayes approach
Syllabus
First part: Resampling techniques with R: 1.- Introduction to the non-parametric Bootstrap 2.- The Bootstrap Paradigm 3.- Bootstrap Confidence Intervals 4.- Permutation and Bootstrap Test 5.- Practicals with R. Second Part: Environmental Case Studies 1.- Small area estimation using linear models: estimation of the number of hectares occupied by fruit trees in Navarra, Spain 1.1 Introduction 1.2. Theoretical model. Inference and Validation 1.3 Practical resolution in R 2.- Spatial Statistics for Environmental Epidemiology: disease mapping using an Empirical Bayes approach 2.1. Introduction. 2.2 A Poisson-Normal Mixed Model 2.3 PQL Inference 2.4 Analysis of mortality data
Language of instruction
English
Further Comments
Study Materials
The course is taught only once.
The course is taught in blocks.
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