Environmental risk directly affects the financial stability of banks since they bear the financial consequences of the loss of liquidity of the entities to which they lend and of the financial penalties imposed resulting from the failure to comply with regulations and for actions taken that are harmful to the natural environment.
Environmental risk directly affects the financial stability of banks since they bear the financial consequences of the loss of liquidity of the entities to which they lend and of the financial penalties imposed resulting from the failure to comply with regulations and for actions taken that are harmful to the natural environment.
Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them.
Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them.
Any enquiry into the nature, performance, role, demerits, growth, efficiency, or other aspects of financial services such as banking and insurance activities, requires rigorous estimates of their economic output, i.
Any enquiry into the nature, performance, role, demerits, growth, efficiency, or other aspects of financial services such as banking and insurance activities, requires rigorous estimates of their economic output, i.
This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics, different financial problems, and other scenarios in which these recently developed statistical models have been applied in recent years.
This work is a detailed description of different discrete and continuous univariate and multivariate distributions with applications in economics, different financial problems, and other scenarios in which these recently developed statistical models have been applied in recent years.
The subject of this textbook is to act as an introduction to data science / data analysis applied to finance, using R and its most recent and freely available extension libraries.
The subject of this textbook is to act as an introduction to data science / data analysis applied to finance, using R and its most recent and freely available extension libraries.
Since a major source of income for many countries comes from exporting commodities, price discovery and information transmission between commodity futures markets are key issues for continued economic development.
Since a major source of income for many countries comes from exporting commodities, price discovery and information transmission between commodity futures markets are key issues for continued economic development.
Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods.
Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods.
ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs.
ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs.
This insightful and timely volume provides a succinct, expert-led introduction to the latest developments in advanced econometric methodologies in the context of tourism demand modelling and forecasting.
This insightful and timely volume provides a succinct, expert-led introduction to the latest developments in advanced econometric methodologies in the context of tourism demand modelling and forecasting.
This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions.
This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions.
Statistical Programming in SAS Second Edition provides a foundation for programming to implement statistical solutions using SAS, a system that has been used to solve data analytic problems for more than 40 years.
Statistical Programming in SAS Second Edition provides a foundation for programming to implement statistical solutions using SAS, a system that has been used to solve data analytic problems for more than 40 years.
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods.
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods.
While women's cricket, and women's sport in general, has gained enormously in popularity in terms of both spectators and TV audiences, comparatively little is known about it and its participants, and there are few, if any, quantitative assessments of the game.
While women's cricket, and women's sport in general, has gained enormously in popularity in terms of both spectators and TV audiences, comparatively little is known about it and its participants, and there are few, if any, quantitative assessments of the game.
Doing Statistical Analysis looks at three kinds of statistical research questions - descriptive, associational, and inferential - and shows students how to conduct statistical analyses and interpret the results.
Doing Statistical Analysis looks at three kinds of statistical research questions - descriptive, associational, and inferential - and shows students how to conduct statistical analyses and interpret the results.
