Statistical Issues
Preface
How to read
Structure
Software
Acknowledgments
I Introduction
1
Introduction
II Statistics
2
Statistical Concepts
III Inference
3
Statistical Inference
3.1
Classical Inference Techniques
3.2
Bayesian Inference Techniques
IV Modelling
4
Introduction {mod_intro}
4.1
Example one
4.2
Generalized additive models
4.3
GAM
4.4
GAM
4.5
Practice MGCV
4.5.1
Basics of gam model
4.5.2
Smoothing several variables
4.6
Survival Analysis
4.7
sub1
4.8
sub2
V Programming
5
Final Words
VI Mathematics
6
Linear Algebra
6.1
Linear Algebra Concepts
6.1.1
Linear Transformation
6.1.2
Change of Basis
6.1.3
Change of Basis for Linear Transformations
6.1.4
Eigenvalues and Eigenvectors
6.1.5
Cauchy–Schwartz inequality
7
here
8
Newton-Raphson and Gradient Descent
9
Here we go
References
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Statistical Issues
3.2
Bayesian Inference Techniques
Rejection sampling
Importance sampling
Markov chain Monte Carlo
Gibbs sampling
Metropolis Hasting
Laplace Approximation
Integrated nested Laplace approximation
Variational Bayes