Pathwise estimation and inference for diffusion market models discusses contemporary techniques for inferring, from options and bond prices, the market participants' aggregate view on important financial parameters such as implied volatility, discount rat.
Nikolai Gogol
Nikolai Blaum
Nikolai Bukharin
Dominic Nikolai Ashen
Nikolai Vatin
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Evreinov
Nikolaï Von Bismark
An enchanting exploration of the creative inspiration of the bloomsbury set on kim jones’s artistic direction of the fashion house fendi.
Nikolai Gogol
Nikolai Gogol
Dominic Nikolai Ashen
Dominic Nikolai Ashen
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Huke
Nikolai Gogol
Nikolai Gogol
Dominic Nikolai Ashen
Dezhnev Nikolai Borisovich
Nikolai Genov
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Schmiederer
St. Nikolai (Velimirovic)
Nikolai Popov
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Nikolai Gogol
Nikolai Gogol
Nikolai Vatin
Nikolai Gogol
Nikolai M. Rubtsov
This book presents new data on combustion processes for practical applications, discussing fire safety issues in the development of flame arresters and the use of noble metals in hydrogen recombiners for nuclear power plants.
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Genov
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Nikolai Gogol
Dominic Nikolai Ashen
Nikolai Gogol
Michèle Nikolaï
Nikolai Gogol
Nikolai Gogol
Nikolai Vatin
Nikolai Gogol
Nikolai Gogol
Nikolai Nikolai Gogol
Scott M. Lynch
For social scientists, it is often confusing how to determine when missing data is a problem in analyses and how to handle it.
Taylor Arnold
A computational approach to statistical learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods.
Michael Gil
Intended for specialists in functional analysis and stability theory, this work presents a systematic exposition of estimations for norms of operator-valued functions, and applies the estimates to spectrum perturbations of linear operators and stability t.
Taylor Arnold
A computational approach to statistical learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods.
Markus Frhlich
John Olusegun Ogundare
Provides a modern approach to least squares estimation and data analysis for undergraduate land surveying and geomatics programsrich in theory and concepts, this comprehensive book on least square estimation and data analysis provides e.
Masafumi Akahira
Zhengming Wang
Measurement data modeling and parameter estimation integrates mathematical theory with engineering practice in the field of measurement data processing.
Andreas Quatember
This book emphasizes that artificial or pseudo-populations play an important role in statistical surveys from finite universes in two manners: firstly, the concept of pseudo-populations may substantially improve users understand.
J. N. K. Rao
Praise for the first edition "this pioneering work, in which rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic...
Emilia Mendes
Harry L. Van Trees
Harry L. Van Trees
Hani S. Mahmassani
A. P. Korostelev
A lucid presentation of modern probability theory based on measure theoretic approach with examples.
Gavin J. S. Ross
Paul P. Biemer
Combining theoretical, methodological, and practical aspects, latent class analysis of survey error successfully guides readers through the accurate interpretation of survey results for quality evaluation and improvement.
John E. Doherty
David W. Scott
Written to convey an intuitive feel for both theory and practice, its main objective is to illustrate what a powerful tool density estimation can be when used not only with univariate and bivariate data but also in the higher dimensions of trivariate and .
Yonina C. Eldar
Adriaan van den Bos
The subject of this book is estimating parameters of expectation models of statistical observations.
Jiti Gao
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years.
Jean-Claude Bertein
Nagoya-shi (Japan)
Richard M. Royall
George B. Dresser
Efi Pagitsas
William T. Steffens
Betty S. Kwok
Patricia Ann Tracey
Anil Kashyap
Dennis J. Aigner
Montana. Highway Department Highway Planning Survey
Harry Bridgman Pulsifer