A01=Gidon Eshel
Accuracy and precision
Addition
Age Group_Uncategorized
Age Group_Uncategorized
Amplitude
Arithmetic
Author_Gidon Eshel
Autocorrelation
Autocovariance
automatic-update
Autoregressive model
Basis (linear algebra)
Big O notation
Calculation
Category1=Non-Fiction
Category=PBF
Category=PBT
Climatology
Coefficient
Confidence interval
COP=United States
Covariance matrix
Cross-covariance
Cumulative distribution function
Data set
Degrees of freedom (statistics)
Delivery_Delivery within 10-20 working days
Dimension
Eigenvalues and eigenvectors
Empirical orthogonal functions
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
Equation
Estimation
Expected value
Fourier
Fundamental theorem of linear algebra
Gaussian elimination
Graduate school
Identity matrix
Inverse problem
Language_English
Least squares
Likelihood function
Linear algebra
Linear combination
Linear independence
MATLAB
Norm (mathematics)
Normal distribution
Null hypothesis
Order of magnitude
Orthogonality
Orthonormality
Outer product
PA=Available
Parameter
Percentage
Phenomenon
Prediction
Price_€100 and above
Probability
Probability distribution
PS=Active
Quantity
Random variable
Rank (linear algebra)
Real number
Regression analysis
Row and column spaces
Scientific notation
Simulink
Sine wave
Singular value
softlaunch
Special case
Square root
Standard deviation
Statistical significance
Subset
Summation
Time series
Transpose
Variable (mathematics)
Variance
Vector space
Product details
- ISBN 9780691128917
- Weight: 567g
- Dimensions: 152 x 235mm
- Publication Date: 25 Dec 2011
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Hardback
- Language: English
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A severe thunderstorm morphs into a tornado that cuts a swath of destruction through Oklahoma. How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China. How do we characterize the spread of the flu, potentially preventing an epidemic? The way to answer important questions like these is to analyze the spatial and temporal characteristics - origin, rates, and frequencies - of these phenomena. This comprehensive text introduces advanced undergraduate students, graduate students, and researchers to the statistical and algebraic methods used to analyze spatiotemporal data in a range of fields, including climate science, geophysics, ecology, astrophysics, and medicine. Gidon Eshel begins with a concise yet detailed primer on linear algebra, providing readers with the mathematical foundations needed for data analysis. He then fully explains the theory and methods for analyzing spatiotemporal data, guiding readers from the basics to the most advanced applications. This self-contained, practical guide to the analysis of multidimensional data sets features a wealth of real-world examples as well as sample homework exercises and suggested exams.
Gidon Eshel is Bard Center Fellow at Bard College.
