Probability and statistics

Applied Mathematics with Open-source Software: Operational Research Problems with Python and R is aimed at a broad segment of readers who wish to learn how to use open-source software to solve problems in applied mathematics.

Stochastic Differential Equations and Diffusion Processes

Using Statistics to Understand the Environment covers all the basic tests required for environmental practicals and projects and points the way to the more advanced techniques that may be needed in more complex research designs.

This book provides an example of a thorough statistical treatment of ocean wave data in space and time.

This book introduces basic computing skills designed for industry professionals without a strong computer science background.

A step-by-step guide to computing and graphics in regression analysis In this unique book, leading statisticians Dennis Cook and Sanford Weisberg expertly blend regression fundamentals and cutting-edge graphical techniques.

Gather and analyze data successfully, identify trends, and then create overarching strategies and actionable next steps - all through Excel.

This monograph presents smooth, unified, and generalized fractional programming problems, particularly advanced duality models for discrete min-max fractional programming.

Originally published in 1966 On the Syllogism and Other Logical Writings assembles for the first time the five celebrated memoirs of Augustus De Morgan on the syllogism.

Data Analytics: A Small Data Approach is suitable for an introductory data analytics course to help students understand some main statistical learning models.

Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling.

With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs).

This textbook, now in its third edition, offers a practical introduction to probability with statistical applications, covering material for both a first and second undergraduate probability course.

This book brings together carefully selected, peer-reviewed works on mathematical biology presented at the BIOMAT International Symposium on Mathematical and Computational Biology, which was held at the Institute of Numerical Mathematics, Russian Academy of Sciences, in October 2017, in Moscow.

The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena.

Methodologies and recipes to regularize any machine learning and deep learning model using cutting-edge technologies such as stable diffusion, Dall-E and GPT-3Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn to diagnose the need for regularization in any machine learning modelRegularize different ML models using a variety of techniques and methodsEnhance the functionality of your models using state of the art computer vision and NLP techniquesBook DescriptionRegularization is an infallible way to produce accurate results with unseen data, however, applying regularization is challenging as it is available in multiple forms and applying the appropriate technique to every model is a must.

Praise for the First Edition This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one s personal library.

Synergetic Economics presents a new advance in analytical economics.

The stochastic Maxwell equations play an essential role in many fields, including fluctuational electrodynamics, statistical radiophysics, integrated circuits, and stochastic inverse problems.

Dieses Buch ist die erste fachübergreifende Einführung in die Kombinatorik in deutscher Sprache und umfasst Gesetzmäßigkeiten, Rechenregeln, Anwendungen sowie 50 Übungsaufgaben mit Lösungen.

Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook.

Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data.

This title is written for the numerate nonspecialist, and hopes to serve three purposes.

The first edition of this excellent handbook was extremely well received by both students and lecturers alike.

This short monograph provides a synthesis of new research on sampling designs that are dependent on sample moments or the order statistics of auxiliary variables.

This book is devoted to Corrado Gini, father of the Italian statistical school.

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The Encyclopedic Dictionary of International Finance and Banking is a practical reference of proven techniques, strategies, and approaches.

Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years.

Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation discusses generalized properties of Lp-estimators.

All techniques illustrated on data sets relevant to insurance; SAS code and output, data sets, exercise solutions on website

The Mathematics of Finance has become a hot topic ever since the discovery of the Black-Scholes option pricing formulas in 1973.

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Game Theory for Networks (GameNets 2012) held in Vancouver, Canada, May 24-26, 2012.

Mortality improvements, uncertainty in future mortality trends and the relevant impact on life annuities and pension plans constitute important topics in the field of actuarial mathematics and life insurance techniques.

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed.

Techniques for interpreting commonly used discrete choice models, illustrated with extensive examples including replication code and data.

This book presents broadly applicable methods for the large deviation and moderate deviation analysis of discrete and continuous time stochastic systems.

The progress of science and technology has placed Queueing Theory among the most popular disciplines in applied mathematics, operations research, and engineering.

Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment.

Introduction to Probability, Second Edition, discusses probability theory in a mathematically rigorous, yet accessible way.

This is a masterly introduction to the modern, and rigorous, theory of probability.

This book constitutes the refereed post-conference proceedings of the 12th International Conference on Wireless and Satellite Services, WiSATS 2021, held in Nanjing, China, in September 2020.

This Volume contains the Keynote, Invited and Full Contributed papers presented at COMPSTAT 2000.

ENVIRONMENTALSTATS for S-PLUS, a new add-on module to S-PLUS, is the first comprehensive software package for environmental scientists, engineers, and regulators.

Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry.

This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain.

Since publication of the first edition in 1992, the field of survey sampling has grown considerably.