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This text presents key topics in mathematical statistics in a rigorous yet accessible manner. It covers aspects of probability, distribution theory, and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models and computationally intensive inferential techniques. The text challenges the more mathematically inclined students while providing an approachable explanation of advanced statistical concepts for students who struggle with existing texts.
This text presents key topics in mathematical statistics in a rigorous yet accessible manner. It covers aspects of probability, distribution theory, and random processes that are fundamental to a proper understanding of inference. The book also discusses the properties of estimators constructed from a random sample of ends, with sections on methods for estimating parameters in time series models and computationally intensive inferential techniques. The text challenges the more mathematically inclined students while providing an approachable explanation of advanced statistical concepts for students who struggle with existing texts.
Miltiadis Mavrakakis obtained his PhD in Statistics at LSE under the supervision of Jeremy Penzer. His first job was as a teaching fellow at LSE, taking over course ST202 and completing this book in the process. He splits his time between lecturing (at LSE, Imperial College London, and the University of London International Programme) and his applied statistical work. Milt is currently a Senior Analyst at Smartodds, a sports betting consultancy, where he focuses on the statistical modelling of sports and financial markets. He lives in London with his wife, son, and daughter.
Jeremy Penzer first post-doc job was as a research assistant at the London School of Economics. Jeremy went on to become a lecturer at LSE and to teach the second year statistical inference course (ST202) that formed the starting point for this book. While working at LSE, his research interests were time series analysis and computational statistics. After 12 years as an academic, Jeremy shifted career to work in financial services. He is currently Chief Marketing and Analytics Officer for Capital One Europe (plc). Jeremy lives just outside Nottingham with his wife and two daughters.
1. Introduction
2. Probability
3. Random Variables and Univariate Distributions
4. Multivariate Distributions
5. Conditional Distributions
6. Statistical Models
7. Sample Moments and Quantiles
8. Estimation, Testing, and Prediction
9. Likelihood-based Inference
10. Inferential Theory
11. Bayesian Inference
12. Simulation Methods
| Erscheinungsjahr: | 2022 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 444 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9780367749125 |
| ISBN-10: | 0367749122 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Penzer, Jeremy
Mavrakakis, Miltiadis C. |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 230 x 154 x 24 mm |
| Von/Mit: | Jeremy Penzer (u. a.) |
| Erscheinungsdatum: | 26.09.2022 |
| Gewicht: | 0,67 kg |
Miltiadis Mavrakakis obtained his PhD in Statistics at LSE under the supervision of Jeremy Penzer. His first job was as a teaching fellow at LSE, taking over course ST202 and completing this book in the process. He splits his time between lecturing (at LSE, Imperial College London, and the University of London International Programme) and his applied statistical work. Milt is currently a Senior Analyst at Smartodds, a sports betting consultancy, where he focuses on the statistical modelling of sports and financial markets. He lives in London with his wife, son, and daughter.
Jeremy Penzer first post-doc job was as a research assistant at the London School of Economics. Jeremy went on to become a lecturer at LSE and to teach the second year statistical inference course (ST202) that formed the starting point for this book. While working at LSE, his research interests were time series analysis and computational statistics. After 12 years as an academic, Jeremy shifted career to work in financial services. He is currently Chief Marketing and Analytics Officer for Capital One Europe (plc). Jeremy lives just outside Nottingham with his wife and two daughters.
1. Introduction
2. Probability
3. Random Variables and Univariate Distributions
4. Multivariate Distributions
5. Conditional Distributions
6. Statistical Models
7. Sample Moments and Quantiles
8. Estimation, Testing, and Prediction
9. Likelihood-based Inference
10. Inferential Theory
11. Bayesian Inference
12. Simulation Methods
| Erscheinungsjahr: | 2022 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 444 |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9780367749125 |
| ISBN-10: | 0367749122 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Penzer, Jeremy
Mavrakakis, Miltiadis C. |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 230 x 154 x 24 mm |
| Von/Mit: | Jeremy Penzer (u. a.) |
| Erscheinungsdatum: | 26.09.2022 |
| Gewicht: | 0,67 kg |
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