Information Geometry: Near Randomness and Near IndependenceSpringer Science & Business Media, 2021 |
Contents
Mathematical Statistics and Information Theory | 1 |
Introduction to Riemannian Geometry | 19 |
Information Geometry | 31 |
Information Geometry of Bivariate Families | 55 |
group headed by Andrew Doig of the Manchester Interdisciplinary Biocentre | 76 |
Neighbourhoods of Poisson Randomness Independence | 108 |
Cosmological Voids and Galactic Clustering | 119 |
Amino Acid Clustering | 138 |
Other editions - View all
Information Geometry: Near Randomness and Near Independence Khadiga Arwini,C. T. J. Dodson Limited preview - 2008 |
Information Geometry: Near Randomness and Near Independence Khadiga Arwini,C. T. J. Dodson No preview available - 2008 |
Information Geometry: Near Randomness and Near Independence Khadiga Arwini,C. T. J. Dodson No preview available - 2008 |
Common terms and phrases
3-manifold a-connections a-curvature tensor a-Ricci tensor a-scalar curvature a₁ affine immersion amino acids Arwini bivariate gamma distribution bivariate Gaussian C.T.J. Dodson clustering coefficient of variation correlation coefficient corresponds covariance curve cv(x defined distances entropy equation exponential distribution exponential family fibre networks Figure Fisher information metric Fisher metric Freund galaxies gamma density functions gamma distribution gamma manifold Gaussian density functions geodesic given ij,k independent components information geometry log-Gaussian M₁ marginal functions Mathematical maximum likelihood McKay bivariate gamma mutually dual n-manifold natural coordinate system points Poisson process Poisson random polygon pore porous media potential function probability density functions Proposition random variables Riemannian manifolds scalar curvature sequence smooth standard deviation stochastic structure submanifold tangent vector tions unit mean variance vector field void αι βι σι ψ α1 ψ α2