In this “course” I will put all the materials which are still not completed-enough to be a stand-alone course.
Curriculum
- 12 Sections
- 72 Lessons
- Lifetime
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- Survival Analysis11
- 1.1Notes (PDF)
- 1.2Intro to Survival Analysis
- 1.3Simple ML Example
- 1.4Survival function role in Maximum Likelihood
- 1.5Kaplan Meier (KM) & Nelson Aalen (NA)
- 1.6Mean & Restricted Mean vs. Median
- 1.7Cox Proportional Hazard
- 1.8Deriving the Partial Likelihood
- 1.9Breslow Estimator for the Baseline Hazard
- 1.10Accelerated Failure Time (AFT)
- 1.11AFT vs. CoxPH
- Expectation Maximization (EM)5
- Multiple Hypothesis Testing7
- Computational Statistics11
- 4.1Gauss Newton – Non Linear Least Squares
- 4.2Riemann Sum, Rejection Sampling, Importance Sampling – Part 1
- 4.3Riemann Sum, Rejection Sampling, Importance Sampling – Part 2
- 4.4Rejection Sampling – Bounding Constant
- 4.5Rejection Sampling – Proof
- 4.6Sampling Importance Resampling (SIR)
- 4.7Profile Likelihood
- 4.8Profile Likelihood – what is a profile?
- 4.9Profile Likelihood – simpler examples
- 4.10Laplace’s Method
- 4.11Random Sampling – Uniform & Inverse Transform
- Gaussian Process Regression5
- Other5
- Factor Analysis9
- 7.1Material
- 7.2(Exploratory) Factor Analysis – Introduction
- 7.3(Exploratory) Factor Analysis – Estimation
- 7.4(Exploratory) Factor Analysis – Rotation
- 7.5(Exploratory) Factor Analysis – Code in R
- 7.6Exploratory vs. Confirmatory Factor Analysis
- 7.7(Confirmatory) Factor Analysis – Code in R
- 7.8SEM – Structural Equations Modelling
- 7.9SEM – Code in R
- Time Series Analysis7
- Quantile Regression3
- Clustering1
- Copulas2
- MCMC6
