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Quantitative Analysis
Parallel Processing
Numerical Analysis
C++ Multithreading
Python for Excel
Python Utilities
Services
Author
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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.
a. Structure of the model with unknown parameters.
b. Recursive formula for posterior joint distribution.
c. Marginal distribution of mean.
d. Marginal distribution of precision.
D. Hierarchical analysis of normal model with known variance.
V. Implementation tools.
VI. Basic Math II.
VII. Implementation tools II.
VIII. Bibliography
Notation. Index. Contents.

Marginal distribution of precision.


imilarly to the previous section we calculate distribution of the precision only. We integrate over the mean direction MATH MATH MATH The above expression has the form of the gamma distribution ( Gamma distribution ), therefore, MATH





Notation. Index. Contents.


















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