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 | Introduction. | Slides 1 | ||
| 06.01 | 2.3-2.5 | General concepts for lifetime modeling. | Slides 2 | |
| 09.01 | 2.6, 2.9-2.14 | Parametric families of Lifetime distributions. | Slides 2, Slides 3 | |
| 13.01 | (2.17) | Gumbel distribution. Log-location-scale families | Slides 3, Slides 4 (revised 11.01) | Extreme value distribution, More on log-location-scale families |
| 16.01 | 11.1-11.3.3, 11.3.5 | Censoring; empirical survival function; Kaplan-Meier estimator. | Slides 5 | |
| 20.01 | 11.3.5 | More on Kaplan-Meier estimator; detailed look at MINITAB example. | Slides 5 | |
| 23.01 | 11.3.6 | The Nelson-Aalen estimator. More properties of the exponential distribution | Slides 6 | About the Exponential Distribution, Poisson Process, Total Time on Test and Barlow-Proschan's Test. |
| 27.01 | 11.3.7 | More properties of the exponential distribution, TTT-plot, the logrank test | Slides 7 | |
| 29.01 | 11.3.7 | TTT-plot, Barlow-Proschan's test, the logrank test (continued). | Slides 7 | |
| 03.02 | 11.3.7 | Finish TTT-plot, Barlow-Proschan's test. New: the logrank test. Start with inference in Parametric models | Slides 7,Slides 8 | |
| 06.02 | 11.4 | Continue with inference in parametric models | Slides 8,Slides 9 - draft | |
| 10.02 | No lecture | |||
| 13.02 | 11.4 | Continue with inference in parametric models | Slides 9 - draft | The standard confidence interval for positive parameters.,Some likelihood theory. |
| 17.02 | 11.4 | Continue with inference in parametric models. The Weibull model. | Slides 9 - draft | |
| 20.02 | 11.4 | Continue with inference in parametric models. Log-location-scale models. Threshold models (3-parameter Weibull). | Slides 9 - draft, Slides 10 | |
| 24.02 | 11.4 | Exact confidence interval for exponential distribution and type II censoring. Survival regression modeling | Slides 10, Slides 11 | |
| 27.02 | Parametric survival regression. Weibull regression. Cox regression. | Slides 10, Slides 11, Slides 12 | ||
| 03.03 | Cox regression. | Slides 12 | ||
| 06.03 | Cox-regression (cont.) | Slides 12, Slides 13 | Book chapter on survival regression | |
| 10.03 | Discussion of Obligatory Exercise 1; Final lesson on Cox regression | |||
| 13.03 | 12 | Case study on Cox regression; Accelerated life testing | Slides 14 | Case study in Cox regression: Medical data |
| 17.03 | 7.1, 7.2.1, 7.3.1, 7.4.1, 7.4.2 | Recurrent events and repairable systems. The nonhomogeneous Poisson process (NHPP). | Slides 15 | Case study in Cox regression: Reliability |
| 20.03 | 7.4.3 | Nonparametric estimation in repairable systems. Parametric estimation in NHPPs | Slides 15, Slides 16-draft | |
| 24.03 | No lecture | |||
| 27.03 | 7.4.4 | Parametric estimation in NHPPs | Slides 16-draft | |
| 31.03 | 7.4.5 | Trend testing in NHPPs | Slides 16-draft, Slides 17 | |
| 03.04 | No lecture | Vaclav will be in Auditorium B1 from 8:15 to 10:00 to guide the work With Obligatory 2 | ||
| 07.04 | Go through exam exercises (in this order, as far as we get today and next time): 2009 Problem 2 2012 Problems 1,2,4 2010 Problem 2,3 2013 Problem 1 | |||
| 10.04 | Continue with exam exercises - final lecture. | |||