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Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
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I. Basic math.
II. Pricing and Hedging.
III. Explicit techniques.
IV. Data Analysis.
1. Time Series.
2. Classical statistics.
3. Bayesian statistics.
A. Basic idea of Bayesian analysis.
B. Estimating the mean of normal distribution with known variance.
C. Estimating unknown parameters of normal distribution.
D. Hierarchical analysis of normal model with known variance.
a. Joint posterior distribution of mean and hyperparameters.
b. Posterior distribution of mean conditionally on hyperparameters.
c. Marginal posterior distribution of hyperparameters.
i. Distribution of mu conditionally on gamma.
ii. Posterior distribution of gamma.
iii. Prior distribution for gamma.
V. Implementation tools.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Posterior distribution of gamma.

n conclusion, we compute the distribution MATH MATH The last expression does not depend on $\mu$ . Hence, we set $\mu=\hat{y}$ and obtain MATH

Notation. Index. Contents.

Copyright 2007