[ 951MATSASIV14 ] VL Advanced Statistical Inference

Es ist eine neuere Version 2021W dieser LV im Curriculum Master's programme Statistics 2023W vorhanden.
Workload Education level Study areas Responsible person Hours per week Coordinating university
4 ECTS M1 - Master's programme 1. year Statistics Helga Wagner 2 hpw Johannes Kepler University Linz
Detailed information
Pre-requisites keine
Original study plan Master's programme Statistics 2017W
Objectives Knowledge of concepts and results in Mathematical Statistics
Subject asymptotic evaluations: convergence concepts, central limit theorem, consistency, the delta method, asymptotic efficiency

generating a random sample: direct and indirect methods, accept-reject, MCMC, bootstrapping

robustness: break point, M-estimator, influence function

asymptotic tests: Wald, Lagrange multiplier, Chi-square

confidence intervals: pivots, pivoting the cdf, asymptotic intervals

decision theory: loss function, risk function, Bayes risk


Criteria for evaluation Exam
Methods Lecture
Language English
Study material Casella G.and Berger R.L. (2002). Statistical Inference.
Changing subject? No
Corresponding lecture in collaboration with 951MASTPRTV14: VL Probability Theory (4 ECTS) equivalent to
5MSMS2VO: VL Mathematische Statistik II (8 ECTS)
On-site course
Maximum number of participants 100
Assignment procedure Assignment according to priority