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copula narratives
Overall, we see from this book several conclusionary remarks. First that correlation is a limited tool in the analytical toolkit for individuals. That copulas provide a second vantage point, particularly on the insights of the extremes of your life experiences where again interesting model risk applications could quickly be afoot. Last we consider that our life is full of difficult to model phenomena and we should attempt to work with a longer view, and work backwards in designing the things we need to succeed in life. Financially, psychologically, holistically.
In copula narratives we complement ideas from my previous two best-selling books. On probability and statistic concepts in Statistics Topics , to extreme agency and probability visualization in Colors and Numbers . We have a framework for these traditional and more novel dimensions of analysis. Now probability and statistics are already dimensions. But they are linear and parametric.
This book centers on distributions that are both nonparametric, and fluid along the distribution. Applying copula theory to tease out the underlying behavior at the edges of the distribution, can reveal new understandings about a problem and the risks within it.
Introduction
Correlation
1A. Introducing correlation
1B. Pros and cons
1C. Copulas, via taus
Copulas
2A. Multicollinearity, and fundamental monotonicity
2B. Outliers
2C. Archimedean, and independence copulas
Narratives on long-view
3A. Labor market
3B. Solving the stock market
3C. Quasi-retirement, and optimal life
3D. Investing in yourself
Narratives on short-view
4A. Vulnerability
4B. Coronavirus
4C. Mass shootings
4D. Exterminations, and population change
4E. AI’s benefits and dangers
4F. Diversity, equity, inclusion
Life lessons, and conclusion
In copula narratives we complement ideas from my previous two best-selling books. On probability and statistic concepts in Statistics Topics , to extreme agency and probability visualization in Colors and Numbers . We have a framework for these traditional and more novel dimensions of analysis. Now probability and statistics are already dimensions. But they are linear and parametric.
This book centers on distributions that are both nonparametric, and fluid along the distribution. Applying copula theory to tease out the underlying behavior at the edges of the distribution, can reveal new understandings about a problem and the risks within it.
Introduction
Correlation
1A. Introducing correlation
1B. Pros and cons
1C. Copulas, via taus
Copulas
2A. Multicollinearity, and fundamental monotonicity
2B. Outliers
2C. Archimedean, and independence copulas
Narratives on long-view
3A. Labor market
3B. Solving the stock market
3C. Quasi-retirement, and optimal life
3D. Investing in yourself
Narratives on short-view
4A. Vulnerability
4B. Coronavirus
4C. Mass shootings
4D. Exterminations, and population change
4E. AI’s benefits and dangers
4F. Diversity, equity, inclusion
Life lessons, and conclusion
120 pages, Hardcover
Published July 18, 2024
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