Lecture plan and progress

R&H refers to relevant sections in Rausand & Høyland: System Reliability Theory: Models, Statistical Methods, and Applications, 2nd Edition. Wiley 2004.

Date R&H Topic Slides Notes/Supplementary reading
06.01 2.3-2.6, 2.9-2.14 Introduction and motivation. General concepts for lifetime modeling. Slides 1, Slides 2
07.01 2.9-2.14 Parametric families of lifetime distributions. Slides 3 Alternative formula for MTTF
13.01 2.9-2.14, 2.17 Extreme value distributions and the Gumbel distribution. Log-location-scale families. Censoring. Slides 4, Slides 5 Extreme value distributions, More on log-location-scale families
14.01 11.1-11.3.3, 11.3.5 Empirical survival function; Kaplan-Meier estimator. Slides 5 Extra on Kaplan-Meier
20.01 11.3.6 Kaplan-Meier estimator (cont.). Nelson-Aalen estimator. Slides 5, Slides 6 R-programs for KM and NA plot
21.01 11.3.7 Properties of the exponential distribution. Derivation of the Nelson-Aalen estimator. Slides 6 About the Exponential Distribution, Poisson Process, Total Time on Test and Barlow-Proschan's Test.
27.01 11.3.7 Derivation of the Nelson-Aalen estimator (cont.) TTT-plot. Slides 6 Algorithm for TTT and BP
28.01 11.4.3, 11.4.4 Barlow-Proschans test. The logrank test. Introduction to parametric methods. Slides 7 (p. 1-12) Note on the logrank test
03.02 11.4.4 Introduction to parametric methods (cont.) Parametric inference for the exponential model. Slides 7 (rest), Slides 8 The standard confidence interval for positive parameters. Some likelihood theory. R-programs for parametric estimation.
04.02 11.4.5 Parametric inference for the Weibull model. Slides 9
10.02 Inference in log-location-scale models. Threshold models (3-parameter Weibull). Slides 10
11.02 Parametric survival regression. Slides 11 Book chapter on survival regression,
17.02 Parametric survival regression (cont.). Slides 11 Modelling of covariates and factors
18.02 Proportional hazards and Cox-regression. Slides 12 R-codes for Cox-regression and parametric regression with survreg.
24.02 Cox regression (cont.) Model checking in Cox-regression. Case study of Cox-regression. Slides 12 Case study in Cox regression
25.02 12, 7.3.1, 7.4.1, 7.4.2, 7.4.3 Accelerated life testing. Recurrent events and repairable systems. The nonhomogeneous Poisson process (NHPP). Slides 13, Slides 14 Download INSULATE.mwx
02.03 7.3.1, 7.4.1, 7.4.2, 7.4.3 Recurrent events and repairable systems. The nonhomogeneous Poisson process (NHPP). Nonparametric estimation of cumulative ROCOF. Slides 14, p. 1-27
03.03 7.3.1, 7.4.1, 7.4.2, 7.4.3, 7.4.4 Nonparametric estimation of cumulative ROCOF (cont.). Parametric estimation in NHPPs. Slides 14, p. 28-41, Slides 15
09.03 7.4.5 Parametric estimation in NHPPs (cont.), Trend testing in NHPPs. Slides 15, Slides 16
10.03 7.4.5 Trend testing in NHPPs (cont.). TTT-plots for repairable systems. Slides 16.
16.03 NO LECTURE (Obligatory 2)
17.03 NO LECTURE (Obligatory 2)
23.03 7.3.1, 7.3.2, 7.3.3 NO LECTURE (Obligatory 2) Self-study: Renewal processes. Slides 16,
24.03 NO LECTURE (Obligatory 2) Self-study: Unobserved heterogeneity in NHPPs Slides 17, Article on unobserved heterogeneity, Exercise on heterogeneity in HPP.
30.03, 31.03 Go through and discuss topics from exam exercises:
2019, 2: Accelerated testing
2016, 3: log-logistic distribution
2009, 2: Nelson-Aalen for repairable system
2009, 3: Parametric estimation in NHPP
2010, 2: A new cdf F(t)
2012, 1: Parametric estimation with censored data
2012, 2: Kaplan-Meier, logrank, Cox
06.04 Easter break
07.04 Easter break
13.04 Easter break
14.04 Easter break
20.04, 21.04 2014, 1: Weibull regression
2008, 2: Hazard rate, renewal process, NHPP
2015, 1: Nelson-Aalen, Total Time on Test
2005, 1: Cox-regression
2019, 3: NHPP, software reliability
2013, 1: Weibull-regression
2020-03-13, Bo Henry Lindqvist