Data assimilation for the geosciences : from theory to application / Steven J. Fletcher.

Format:

Book

Author/Creator:

Fletcher, Steven J. (Steven James), author.

Contributor:

ebrary, Inc.

Sabin W. Colton, Jr., Memorial Fund.

Language:

English

Subjects (All):

Coding theory.

Earth sciences--Data processing.

Earth sciences.

Physical Description:

1 online resource

polychrome

Place of Publication:

Amsterdam, Netherlands : Elsevier, [2017]

System Details:

text file

Contents:

Front Cover; Data Assimilation for the Geosciences: From Theory to Application; Copyright; Contents; Chapter 1: Introduction; Chapter 2: Overview of Linear Algebra; 2.1 Properties of Matrices; 2.1.1 Matrix Multiplication; 2.1.2 Transpose of a Matrix; 2.1.3 Determinants of Matrices; 2.1.4 Inversions of Matrices; 2.1.5 Rank, Linear Independence and Dependence; 2.1.6 Matrix Structures; 2.2 Matrix and Vector Norms; 2.2.1 Vector Norms; 2.2.2 Matrix Norms; 2.2.3 Conditioning of Matrices; 2.2.4 Matrix Condition Number; 2.3 Eigenvalues and Eigenvectors; 2.4 Matrix Decompositions

2.4.1 Gaussian Elimination and the LU Decomposition2.4.2 Cholesky Decomposition; 2.4.3 The QR Decomposition; 2.4.4 Diagonalization; 2.4.5 Singular Value Decomposition; 2.5 Sherman-Morrison-Woodbury Formula; 2.6 Summary; Chapter 3: Univariate Distribution Theory; 3.1 Random Variables; 3.2 Discrete Probability Theory; 3.2.1 Discrete Random Variables; 3.3 Continuous Probability Theory; 3.4 Discrete Distribution Theory; 3.4.1 Binomial Distribution; 3.4.2 Geometric Distribution; 3.4.3 Poisson Distribution; 3.4.4 Discrete Uniform Distribution

3.5 Expectation and Variance of Discrete Random Variables3.5.1 Mean of the Binomial Distribution; 3.5.2 Mean of the Geometric Distribution; 3.5.3 Mean of the Poisson Distribution; 3.5.4 Mean of the Discrete Uniform Distribution; 3.5.5 Variance of a Discrete Probability Mass Function; 3.5.6 Variance of the Binomial Distribution; 3.5.7 Variance of the Geometric Distribution; 3.5.8 Variance of the Poisson Distribution; 3.5.9 Variance of the Discrete Uniform Distribution; 3.6 Moments and Moment-Generating Functions; 3.6.1 Moment-Generating Functions for Probability Mass Functions

3.6.2 Binomial Distribution Moment-Generating Function3.6.3 Geometric Distribution Moment-Generating Function; 3.6.4 Poisson Moment-Generating Function; 3.6.5 Discrete Uniform Distribution Moment-Generating Function; 3.7 Continuous Distribution Theory; 3.7.1 Gaussian (Normal) Distribution; Calculus-based derivation of the Gaussian distribution; 3.7.2 Moments of the Gaussian Distribution; 3.7.3 Moment-Generating Functions for Continuous Probability Density Functions; Properties of moment-generating functions; 3.7.4 Median of the Gaussian Distribution

3.7.5 Mode of the Univariate Gaussian Distribution3.8 Lognormal Distribution; 3.8.1 Moments of the Lognormal Distribution; 3.8.2 Geometric Behavior of the Lognormal; 3.8.3 Median of the Univariate Lognormal Distribution; 3.8.4 Mode of the Lognormal Distribution; 3.9 Exponential Distribution; 3.10 Gamma Distribution; 3.10.1 Moment-Generating Function for the Gamma Distribution; 3.10.2 Skewness of the Gamma Distribution; 3.10.3 Kurtosis of the Gamma Distribution; 3.10.4 Median of the Gamma Distribution; 3.10.5 Mode of the Gamma Distribution

Notes:

Includes bibliographical references and index.

Electronic reproduction. Palo Alto, Calif. Available via World Wide Web.

Description based on online resource; title from digital title page (viewed on April 05, 2017).

Local Notes:

Acquired for the Penn Libraries with assistance from the Sabin W. Colton, Jr., Memorial Fund.

ISBN:

9780128044841

0128044845

Publisher Number:

99971565803

Access Restriction:

Restricted for use by site license.