| Christopher G. Small, Jinfang Wang - Science - 2003 - 309 pages
This text provides a comprehensive study of nonlinear estimating equations and artificial likelihoods for statistical inference. It contains extensive coverage and comparison ... | |
| Christopher G. Small - Mathematics - 2007 - 131 pages
Many books have been written on the theory of functional equations, but very few help readers solve functional equations in mathematics competitions and mathematical problem ... | |
| Christopher G. Small, Don L. McLeish - Mathematics - 2011 - 270 pages
Explains how Hilbert space techniques cross the boundaries into the foundations of probability and statistics. Focuses on the theory of martingales stochastic integration ... | |
| D.L. McLeish, Christopher G. Small - Mathematics - 2012 - 124 pages
This monograph arose out of a desire to develop an approach to statistical infer ence that would be both comprehensive in its treatment of statistical principles and ... | |
| Christopher G. Small - Mathematics - 2012 - 230 pages
In general terms, the shape of an object, data set, or image can be de fined as the total of all information that is invariant under translations, rotations, and isotropic ... | |
| Randal Douc, Eric Moulines, David Stoffer - Mathematics - 2014 - 551 pages
Designed for researchers and students, Nonlinear Times Series: Theory, Methods and Applications with R Examples familiarizes readers with the principles behind nonlinear time ... | |
| Thomas A. Severini - Mathematics - 2005
This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use ... | |
| F. Liese, Klaus-J. Miescke - Mathematics - 2008 - 677 pages
For advanced graduate students, this book is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner ... | |
| John Miller, David Edelman, John Appleby - Mathematics - 2007 - 312 pages
Featuring international contributors from both industry and academia, Numerical Methods for Finance explores new and relevant numerical methods for the solution of practical ... | |
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