In this “course” I will put all the materials which are still not completed-enough to be a stand-alone course.
Curriculum
- 10 Sections
- 60 Lessons
- Lifetime
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Survival Analysis9
- 3.0Notes (PDF)
- 3.1Intro to Survival Analysis
- 3.2Simple ML Example
- 3.3Survival function role in Maximum Likelihood
- 3.4Kaplan Meier (KM) & Nelson Aalen (NA)
- 3.5Mean & Restricted Mean vs. Median
- 3.6Cox Proportional Hazard
- 3.7Deriving the Partial Likelihood
- 3.8Breslow Estimator for the Baseline Hazard
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Expectation Maximization (EM)5
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Multiple Hypothesis Testing7
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Computational Statistics11
- 6.0Gauss Newton – Non Linear Least Squares
- 6.1Riemann Sum, Rejection Sampling, Importance Sampling – Part 1
- 6.2Riemann Sum, Rejection Sampling, Importance Sampling – Part 2
- 6.3Rejection Sampling – Bounding Constant
- 6.4Rejection Sampling – Proof
- 6.5Sampling Importance Resampling (SIR)
- 6.6Profile Likelihood
- 6.7Profile Likelihood – what is a profile?
- 6.8Profile Likelihood – simpler examples
- 6.9Laplace’s Method
- 6.10Random Sampling – Uniform & Inverse Transform
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Gaussian Process Regression5
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Other5
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Factor Analysis9
- 9.0Material
- 9.1(Exploratory) Factor Analysis – Introduction
- 9.2(Exploratory) Factor Analysis – Estimation
- 9.3(Exploratory) Factor Analysis – Rotation
- 9.4(Exploratory) Factor Analysis – Code in R
- 9.5Exploratory vs. Confirmatory Factor Analysis
- 9.6(Confirmatory) Factor Analysis – Code in R
- 9.7SEM – Structural Equations Modelling
- 9.8SEM – Code in R
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Time Series Analysis5
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Quantile Regression3
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Clustering1
