In this “course” I will put all the materials which are still not completed-enough to be a stand-alone course.
Curriculum
- 10 Sections
- 55 Lessons
- Lifetime
Expand all sectionsCollapse all sections
- Copulas2
- Quantile Regression3
- Expectation Maximization (EM)5
- Multiple Hypothesis Testing7
- Computational Statistics11
- 5.1Gauss Newton – Non Linear Least Squares
- 5.2Riemann Sum, Rejection Sampling, Importance Sampling – Part 1
- 5.3Riemann Sum, Rejection Sampling, Importance Sampling – Part 2
- 5.4Rejection Sampling – Bounding Constant
- 5.5Rejection Sampling – Proof
- 5.6Sampling Importance Resampling (SIR)
- 5.7Profile Likelihood
- 5.8Profile Likelihood – what is a profile?
- 5.9Profile Likelihood – simpler examples
- 5.10Laplace’s Method
- 5.11Random Sampling – Uniform & Inverse Transform
- Gaussian Process Regression5
- 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
- Clustering1
- Other5
