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008 170324t20172017enkd sb 001 0 eng d;

010 a| 2017937771;

015 a| GBB7B43672| bnb;

016 7 a| 0184088442| Uk;

020 a| 9781786301246q| (hardback);

020 a| 1786301245q| (hardback);

020 z| 9781119372226q| (ePub ebook);

020 z| 9781119372219q| (PDF ebook);

035 a| (WaSeSS)ssj0002277620;

042 a| lccopycat;

049 a| EREEa| NEHH;

050 00 a| QE539.2.S73b| C664 2017;

082 04 a| 551.22072/72| 23;

100 1 a| Console, Rodolfo,d| 1944.1| https://id.oclc.org/worldcat/entity/E39PCjthGDmXXfTvPqrcCjgvVC.;

245 10 a| Earthquake occurrenceh| [electronic resource] :b| short- and long-term models and their validation /c| Rodolfo Console, Maura Murru, Giuseppe Falcone.;

300 a| xxi, 138 pages :b| charts ;c| 25 cm;

386 a| Italians2| lcdgt;

490 1 a| Mathematics and statistics series (ISTE). Statistical methods for earthquakes set ;v| volume 1;

504 a| Includes bibliographical references (pages 121-135) and index.;

505 00 t| Foreword --t| Preface --t| Introduction --g| Chapter 1.t| Siesmicity and earthquake catalogues described as point processes --g| 1.1.t| The Gutenberg-Richter law --g| 1.2.t| The time-independent Poisson model --g| 1.3.t| Occurrence rate density as a space-time continuous variable --g| 1.4.t| Time-independent spatial distribution --g| 1.5.t| Clustered seismicity --g| 1.6.t| Epidemic models --g| Chapter 2.t| The likelihood of a hypothesis --g| 2.1.t| The Bayes theorem --g| 2.2.t| Likelihood function --g| 2.3.t| Alternative formulations --g| 2.4.t| Likelihood ratio --g| Chapter 3.t| The likelihood for a model of continuous rate density distribution --g| 3.1.t| The limit case of regions of infinitesimal dimensions --g| 3.2.t| The case of discrete regions --g| 3.3.t| The case of time independence --g| 3.4.t| The likelihood of an epidemic model in a 4-D space of parameters --g| Chapter 4.t| Forecast verification procedures --g| 4.1.t| Scoring procedures --g| 4.2.t| The binary diagrams --g| 4.2.1.t| The ROC diagrams --g| 4.2.2.t| Molchan's error diagram --g| 4.2.3.t| Probability gain --g| 4.2.4.t| R-score --g| 4.3.t| Statistical tests implemented within CSEP --g| 4.3.1.t| Number test or N-test --g| 4.3.2.t| Data-consistency test or L-test --g| 4.3.3.t| S(pace)-test or S-test --g| 4.3.4.t| M(agnitude)-test or M-test --g| Chapter 5.t| Applications of epidemic models --g| 5.1.t| Declustering a catalogue through an epidemic model --g| 5.2.t| Earthquake forecasting --g| 5.3.t| Seismic hazard maps for short-term forecast --g| Chapter 6.t| Long-term earthquake occurrence models --g| 6.1.t| The empirical Gutenberg-Richter law and the time-independent model under the Poisson hypothesis --g| 6.2.t| Statistics of inter-event times --g| 6.3.t| The truncated magnitude distribution --g| 6.4.t| Earthquake rate assessment under a renewal time-dependent model --g| 6.4.1.t| Exponential distribution (under the time-dependent hypothesis) --g| 6.4.2.t| Log-normal distribution --g| 6.4.3.t| Gamma distribution --g| 6.4.4.t| Weibull distribution --g| 6.4.5.t| Double-exponential distribution --g| 6.4.6.t| BPT distribution --g| 6.5.t| Validation and comparison of renewal time-dependent models --g| 6.5.1.t| The likelihood ratio --g| 6.5.2.t| Long-term earthquake records --g| 6.5.3.t| Application of a Monte Carlo procedure --g| 6.5.4.t| Concluding remarks --g| 6.6.t| The Cornell method for time-dependent seismic hazard assessment --g| 6.7.t| Acknowledgments --g| Chapter 7.t| Computer programs and examples of their use --g| 7.1.t| PDE2REC, ZMAP2REC --g| 7.2.t| REC2PDE --g| 7.3.t| SMOOTH --g| 7.4.t| LIKELAQP --g| 7.5.t| LIKSTAQP --g| 7.6.t| BPT --t| Bibliography --t| Index.;

506 a| Available only to authorized users.;

650 0 a| Earthquake predictionx| Statistical methods.;

520 a| "'Earthquake Occurrence' provides the reader with a review of algorithms applicable for modeling seismicity, such as short-term earthquake clustering and pseudo-periodic long-term behavior of major earthquakes. The concept of the likelihood ratio of a set of observations under different hypotheses is applied for comparison among various models. In short-term models, known by the term ETAS, the occurrence space and time rate density of earthquakes is modeled as the sum of two terms, one representing the independent or spontaneous events, and the other representing the activity triggered by previous earthquakes. Examples of the application of such algorithms in real cases are also reported. Dealing with long-term recurrence models, renewal time-dependent models, implying a pseudo-periodicity of earthquake occurrence, are compared with the simple time-independent Poisson model, in which every event occurs regardless of what has occurred in the past. The book also introduces a number of computer codes developed by the authors over decades of seismological research"--Back cover;

538 a| Mode of access: World Wide Web;

650 0 a| Seismologyx| Statistical methods.;

650 0 a| Earthquakesx| Statistical methods.;

650 7 a| Earthquake predictionx| Statistical methods.2| fast0| (OCoLC)fst00900873;

650 7 a| Seismologyx| Statistical methods.2| fast0| (OCoLC)fst01111329;

655 0 a| Electronic books.;

700 1 a| Murru, Maura.;

700 1 a| Falcone, Giuseppec| (Geophysicist).1| https://id.oclc.org/worldcat/entity/E39PBJp64HWfPw3bqxfgT9PG73.;

776 08 i| Ebook version :z| 9781119372226;

949 a| CLICK ON WEB ADDRESSw| ASISh| JOYNER188;

830 0 a| Mathematics and statistics series (ISTE).p| Statistical methods for earthquakes set ;v| v. 1.;

856 40 z| Full text available from Ebook Central - Academic Completeu| https://ebookcentral.proquest.com/lib/eastcarolina/detail.action?docID=4923298;

947 a| (OCoLC)on1004258576;

949 a| CLICK ON WEB ADDRESSw| ASISh| HSL77;

949 a| CLICK ON WEB ADDRESSw| ASISh| JMUSIC60;

596 a| 1 3 4;

998 a| 5320821;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5320821-1001l| JNETm| JOYNERr| Ys| Yt| JNESSBKu| 5/15/2020x| EBOOKz| JERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5320821-2001l| HSLELECm| HSLr| Ys| Yt| HEBKu| 5/15/2020x| EBOOKz| HERESOURCE;

999 a| CLICK ON WEB ADDRESSw| ASISc| 1i| 5320821-3001l| MNETm| JMUSICr| Ys| Yt| MNESSBKu| 5/15/2020x| EBOOKz| JERESOURCE;

Earthquake occurrence short- and long-term models and their validation / Rodolfo Console, Maura Murru, Giuseppe Falcone.

Author/creator	Console, Rodolfo, 1944
Other author	Murru, Maura.
Other author	Falcone, Giuseppe (Geophysicist).
Format	Electronic
Publication Info	London, UK : ISTE, Ltd. ; Hoboken, NJ : Wiley, 2017.
Description	xxi, 138 pages : charts ; 25 cm
Supplemental Content	Full text available from Ebook Central - Academic Complete
Subjects	Earthquake prediction--Statistical methods. Seismology--Statistical methods. Earthquakes--Statistical methods.

Series	Mathematics and statistics series (ISTE). Statistical methods for earthquakes set ; volume 1 Mathematics and statistics series (ISTE). Statistical methods for earthquakes set ; v. 1.
Contents	Foreword -- Preface -- Introduction -- Chapter 1. Siesmicity and earthquake catalogues described as point processes -- 1.1. The Gutenberg-Richter law -- 1.2. The time-independent Poisson model -- 1.3. Occurrence rate density as a space-time continuous variable -- 1.4. Time-independent spatial distribution -- 1.5. Clustered seismicity -- 1.6. Epidemic models -- Chapter 2. The likelihood of a hypothesis -- 2.1. The Bayes theorem -- 2.2. Likelihood function -- 2.3. Alternative formulations -- 2.4. Likelihood ratio -- Chapter 3. The likelihood for a model of continuous rate density distribution -- 3.1. The limit case of regions of infinitesimal dimensions -- 3.2. The case of discrete regions -- 3.3. The case of time independence -- 3.4. The likelihood of an epidemic model in a 4-D space of parameters -- Chapter 4. Forecast verification procedures -- 4.1. Scoring procedures -- 4.2. The binary diagrams -- 4.2.1. The ROC diagrams -- 4.2.2. Molchan's error diagram -- 4.2.3. Probability gain -- 4.2.4. R-score -- 4.3. Statistical tests implemented within CSEP -- 4.3.1. Number test or N-test -- 4.3.2. Data-consistency test or L-test -- 4.3.3. S(pace)-test or S-test -- 4.3.4. M(agnitude)-test or M-test -- Chapter 5. Applications of epidemic models -- 5.1. Declustering a catalogue through an epidemic model -- 5.2. Earthquake forecasting -- 5.3. Seismic hazard maps for short-term forecast -- Chapter 6. Long-term earthquake occurrence models -- 6.1. The empirical Gutenberg-Richter law and the time-independent model under the Poisson hypothesis -- 6.2. Statistics of inter-event times -- 6.3. The truncated magnitude distribution -- 6.4. Earthquake rate assessment under a renewal time-dependent model -- 6.4.1. Exponential distribution (under the time-dependent hypothesis) -- 6.4.2. Log-normal distribution -- 6.4.3. Gamma distribution -- 6.4.4. Weibull distribution -- 6.4.5. Double-exponential distribution -- 6.4.6. BPT distribution -- 6.5. Validation and comparison of renewal time-dependent models -- 6.5.1. The likelihood ratio -- 6.5.2. Long-term earthquake records -- 6.5.3. Application of a Monte Carlo procedure -- 6.5.4. Concluding remarks -- 6.6. The Cornell method for time-dependent seismic hazard assessment -- 6.7. Acknowledgments -- Chapter 7. Computer programs and examples of their use -- 7.1. PDE2REC, ZMAP2REC -- 7.2. REC2PDE -- 7.3. SMOOTH -- 7.4. LIKELAQP -- 7.5. LIKSTAQP -- 7.6. BPT -- Bibliography -- Index.
Abstract	"'Earthquake Occurrence' provides the reader with a review of algorithms applicable for modeling seismicity, such as short-term earthquake clustering and pseudo-periodic long-term behavior of major earthquakes. The concept of the likelihood ratio of a set of observations under different hypotheses is applied for comparison among various models. In short-term models, known by the term ETAS, the occurrence space and time rate density of earthquakes is modeled as the sum of two terms, one representing the independent or spontaneous events, and the other representing the activity triggered by previous earthquakes. Examples of the application of such algorithms in real cases are also reported. Dealing with long-term recurrence models, renewal time-dependent models, implying a pseudo-periodicity of earthquake occurrence, are compared with the simple time-independent Poisson model, in which every event occurs regardless of what has occurred in the past. The book also introduces a number of computer codes developed by the authors over decades of seismological research"--Back cover
Bibliography note	Includes bibliographical references (pages 121-135) and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Issued in other form	Ebook version : 9781119372226
Genre/form	Electronic books.
LCCN	2017937771
ISBN	9781786301246 (hardback)
ISBN	1786301245 (hardback)
ISBN	(ePub ebook)
ISBN	(PDF ebook)

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