0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R1,000 - R2,500 (2)
  • R2,500 - R5,000 (6)
  • R5,000 - R10,000 (1)
  • -
Status
Brand

Showing 1 - 9 of 9 matches in All Departments

Statistics and Finance - An Introduction (Hardcover, 1st Corrected ed. 2004. Corr. 2nd printing 2006): David Ruppert Statistics and Finance - An Introduction (Hardcover, 1st Corrected ed. 2004. Corr. 2nd printing 2006)
David Ruppert
R4,690 Discovery Miles 46 900 Ships in 12 - 17 working days

This book emphasizes the applications of statistics and probability to finance. The basics of these subjects are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance and it introduces the newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at advanced undergraduates and masters students. Those in the finance industry can use it for self-study.

Transformation and Weighting in Regression (Hardcover): Raymond J Carroll, David Ruppert Transformation and Weighting in Regression (Hardcover)
Raymond J Carroll, David Ruppert
R5,013 Discovery Miles 50 130 Ships in 12 - 17 working days

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research.

While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Transformation and Weighting in Regression (Paperback): Raymond J Carroll, David Ruppert Transformation and Weighting in Regression (Paperback)
Raymond J Carroll, David Ruppert
R1,834 Discovery Miles 18 340 Ships in 12 - 17 working days

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research. While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Statistics and Data Analysis for Financial Engineering - with R examples (Hardcover, 2nd ed. 2015): David Ruppert, David S... Statistics and Data Analysis for Financial Engineering - with R examples (Hardcover, 2nd ed. 2015)
David Ruppert, David S Matteson
R3,365 Discovery Miles 33 650 Ships in 12 - 17 working days

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Semiparametric Regression with R (Paperback, 1st ed. 2018): Jaroslaw Harezlak, David Ruppert, Matt P. Wand Semiparametric Regression with R (Paperback, 1st ed. 2018)
Jaroslaw Harezlak, David Ruppert, Matt P. Wand
R3,523 Discovery Miles 35 230 Ships in 10 - 15 working days

This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts. The authors assemble a broad range of semiparametric regression R analyses and put them in a form that is useful for applied researchers. There are chapters devoted to penalized spines, generalized additive models, grouped data, bivariate extensions of penalized spines, and spatial semi-parametric regression models. Where feasible, the R code is provided in the text, however the book is also accompanied by an external website complete with datasets and R code. Because of its flexibility, semiparametric regression has proven to be of great value with many applications in fields as diverse as astronomy, biology, medicine, economics, and finance. This book is intended for applied statistical analysts who have some familiarity with R.

Statistics and Data Analysis for Financial Engineering (Paperback, 2011 ed.): David Ruppert Statistics and Data Analysis for Financial Engineering (Paperback, 2011 ed.)
David Ruppert
R2,895 Discovery Miles 28 950 Ships in 10 - 15 working days

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and analytic methods for modeling and diagnosing modeling errors. Despite some overlap with the author's undergraduate textbook Statistics and Finance: An Introduction, this book differs from that earlier volume in several important aspects: it is graduate-level; computations and graphics are done in R; and many advanced topics are covered, for example, multivariate distributions, copulas, Bayesian computations, VaR and expected shortfall, and cointegration.
The prerequisites are basic statistics and probability, matrices and linear algebra, and calculus.
Some exposure to finance is helpful.

Semiparametric Regression (Hardcover, New): David Ruppert, M. P. Wand, R. J. Carroll Semiparametric Regression (Hardcover, New)
David Ruppert, M. P. Wand, R. J. Carroll
R3,482 Discovery Miles 34 820 Ships in 12 - 17 working days

Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression analysis helps make sense of such data in application areas that include engineering, finance, medicine and public health. The book is geared towards researchers and professionals with little background in regression as well as statistically oriented scientists (biostatisticians, econometricians, quantitative social scientists, and epidemiologists) with knowledge of regression and the desire to begin using more flexible semiparametric models.

Measurement Error in Nonlinear Models - A Modern Perspective, Second Edition (Hardcover, 2nd edition): Raymond J Carroll, David... Measurement Error in Nonlinear Models - A Modern Perspective, Second Edition (Hardcover, 2nd edition)
Raymond J Carroll, David Ruppert, Leonard A Stefanski, Ciprian M Crainiceanu
R3,783 Discovery Miles 37 830 Ships in 12 - 17 working days

It's been over a decade since the first edition of "Measurement Error in Nonlinear Models" splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available.

"What's new in the Second Edition?"

- Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques

- A new chapter on longitudinal data and mixed models

- A thoroughly revised chapter on nonparametric regression and density estimation

- A totally new chapter on semiparametric regression

- Survival analysis expanded into its own separate chapter

- Completely rewritten chapter on score functions

- Many more examples and illustrative graphs

- Unique data sets compiled and made available online

In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you're looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.

Semiparametric Regression (Paperback): David Ruppert, M. P. Wand, R. J. Carroll Semiparametric Regression (Paperback)
David Ruppert, M. P. Wand, R. J. Carroll
R1,474 Discovery Miles 14 740 Ships in 12 - 17 working days

Science abounds with problems where the data are noisy and the answer is not a straight line. Semiparametric regression analysis helps make sense of such data in application areas that include engineering, finance, medicine and public health. The book is geared towards researchers and professionals with little background in regression as well as statistically oriented scientists (biostatisticians, econometricians, quantitative social scientists, and epidemiologists) with knowledge of regression and the desire to begin using more flexible semiparametric models.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
First Aid Dressing No 3
R5 R1 Discovery Miles 10
Jurassic World: Camp Cretaceous - Season…
DVD  (1)
R133 Discovery Miles 1 330
Croxley Artist Fineliner Set - Black (5…
R69 R59 Discovery Miles 590
Dog's Life Ballistic Nylon Waterproof…
R999 R569 Discovery Miles 5 690
Sunbeam Steam and Spray Iron
R270 Discovery Miles 2 700
Cellphone Ring & Stand [Black]
R22 Discovery Miles 220
Bostik Art & Craft White Glue (100ml)
R51 R33 Discovery Miles 330
Sport Basket Ball Hoop With Stand & Ball
R289 Discovery Miles 2 890
Docking Edition Multi-Functional…
R899 R399 Discovery Miles 3 990
Infantino Animal Counting Book
R170 R159 Discovery Miles 1 590

 

Partners