|
" Recent studies on risk analysis and statistical modeling / "
Teresa A. Oliveira, Christos P. Kitsos, Amílcar Oliveira, Luís Grilo, editors.
| Document Type
|
:
|
BL
|
| Record Number
|
:
|
865184
|
| Title & Author
|
:
|
Recent studies on risk analysis and statistical modeling /\ Teresa A. Oliveira, Christos P. Kitsos, Amílcar Oliveira, Luís Grilo, editors.
|
| Publication Statement
|
:
|
Cham, Switzerland :: Springer,, [2018]
|
| Series Statement
|
:
|
Contributions to statistics
|
| Page. NO
|
:
|
1 online resource
|
| ISBN
|
:
|
3319766058
|
|
|
:
|
: 3319766066
|
|
|
:
|
: 9783319766058
|
|
|
:
|
: 9783319766065
|
|
|
:
|
331976604X
|
|
|
:
|
9783319766041
|
| Bibliographies/Indexes
|
:
|
Includes bibliographical references.
|
| Contents
|
:
|
Intro; Preface; Introduction; Part I: Risk Methodologies and Applications; Part II: Statistical Modeling and Risk Issues in Several Areas; Contents; Part I Risk Methodologies and Applications; Assessment of Maximum A Posteriori Image Estimation Algorithms for Reduced Acquisition Time Medical Positron Emission Tomography Data; 1 Introduction; 2 Statistical Modelling for PET Data; 3 Maximum Likelihood and Maximum a Posteriori Estimation Using an EM Algorithm; 4 Data Description and Assessment Criteria; 5 Experimental Results; 6 Discussion; References; Multifractal Analysis on Cancer Risk.
|
|
|
:
|
1 Introduction2 Indication for Shape Analysis Approach for Wilms Tumors; 2.1 Differentiation Between Different tumor Groups; 2.2 4D-Shape Analysis; 2.3 Mixed Distribution Estimation; 2.3.1 4D Shape Analysis; 2.3.2 Checking of Consistency; 2.3.3 Estimation to Differentiate tumors; 3 Conclusion; References; Traditional Versus Alternative Risk Measures in Hedge Fund Investment Efficiency; 1 Introduction; 2 Literature Overview; 3 Problems of Hedge Funds Efficiency Measurement; 4 Basic Hedge Funds Statistics; 5 Maximum Drawdown Measures and Their Definitions.
|
|
|
:
|
2 Modeling Chromatography Measurements with an Inflated Pareto Distribution2.1 A Brief Description of the Problem and the Data Sets; 2.2 Inflated Pareto Model and ML Estimation; 2.3 Inflated Pareto Models Fitted to the Historical Data Sets; 3 Acceptance Sampling Plans for Inflated Pareto Data; 3.1 Some Preliminaries; 3.2 Design of Variables AS Plans; 3.3 Performance of the Previous Sampling Plans; 3.4 Algorithm for the Implementation of Plan I, for Inflated Pareto Data; 4 Conclusions; References; Risk of Return Levels for Spatial Extreme Events; 1 Introduction.
|
|
|
:
|
5 Case Study II: Regression Modeling of the CBCI6 Conclusions and Future Research; References; On the Application of Sample Coefficient of Variation for Managing Loan Portfolio Risks; 1 Introduction; 2 Properties of Sample Coefficient of Variation; 2.1 Bounds for cv; 2.2 Efficiency of cv; 3 Application of cv for Measuring Concentration Risk in Loan Portfolio; 3.1 Capital Adequacy and Concentration Risk in the Loan Portfolios; 4 An Example; 5 Conclusion; Appendix; References; Acceptance-Sampling Plans for Reducing the Risk Associated with Chemical Compounds; 1 Introduction and Motivation.
|
|
|
:
|
6 Research Results of the Hedge Fund Risk Return Profile7 Conclusions; Appendix; References; Estimating the Extremal Coefficient: A Simulation Comparison of Methods; 1 Introduction; 2 Examples and Estimators; 3 Simulation Study; 4 Application to Real Data; Appendix; References; On a Business Confidence Index and Its Data Analytics:A Chilean Case; 1 Introduction; 2 Business Intelligence; 3 Methodology of the Chilean Business Confidence Index; 3.1 Target Population and Sample Design; 3.2 Data, Interview and Re-interview; 3.3 Customer Survey; 3.4 Building the CBCI; 4 Case Study I: CBCI on 2016.
|
| Abstract
|
:
|
This book provides an overview of the latest developments in the field of risk analysis (RA). Statistical methodologies have long-since been employed as crucial decision support tools in RA. Thus, in the context of this new century, characterized by a variety of daily risks - from security to health risks - the importance of exploring theoretical and applied issues connecting RA and statistical modeling (SM) is self-evident. In addition to discussing the latest methodological advances in these areas, the book explores applications in a broad range of settings, such as medicine, biology, insurance, pharmacology and agriculture, while also fostering applications in newly emerging areas. This book is intended for graduate students as well as quantitative researchers in the area of RA.
|
| Subject
|
:
|
Risk assessment-- Mathematical models.
|
| Subject
|
:
|
BUSINESS ECONOMICS-- Industries-- General.
|
| Subject
|
:
|
Probability statistics.
|
| Subject
|
:
|
Reliability engineering.
|
| Subject
|
:
|
Risk assessment-- Mathematical models.
|
| Dewey Classification
|
:
|
338.5
|
| LC Classification
|
:
|
HD61
|
| Added Entry
|
:
|
Grilo, Luís
|
|
|
:
|
Kitsos, Christos Par.,1951-
|
|
|
:
|
Oliveira, Amilcar
|
|
|
:
|
Oliveira, Teresa
|
| |