Tabla de Contenidos: “…Deontic reasoning: thinking about rulesPragmatic reasoning schemas; Evolutionary approaches to deontic reasoning; Decision-theoretic approaches; Causal reasoning: thinking about how the world works; Causal reasoning about general events; The covariational approach to causal thinking; Prior knowledge and causal models; Causal models theory; Single cases and counterfactual thinking; Summary; Chapter 5 : Explaining reasoning: the classic approaches; Mental logic; Braine and O'Brien's theory of If; Rips' Psycop theory; The theory of mental models; Mental models and conditionals…”

Tabla de Contenidos: “…Al-Fārābī on What Is Known Prior to the Syllogistic Arts in His Introductory Letter, the Five Aphorisms, and the Book of Dialectic Terence J. …”

Tabla de Contenidos: “…[Latin] [Graecum] Monitum in Alteram Orationem antiquam iret in Exsilium Cum iret in Exsilium [Latin] [Graecum] Post Reditum a priore Exsilio Ejusdem post Reditum [Latin] [Graecum] In Dimissionem Chananææ [Graecum] [Latin] In librum, quod Nemo Lædatur nisi a Seipso - Admonitio Liber [Latin] [Graecum] In librum ad eos qui scandalizati sunt ob adversitates - admonitio Ejusdem Liber [Latin] [Graecum] Monitum in Epistolas duas Joannis Chrysostomi ad Innoventium Papam Innocentio Episcopo Romæ [Graecum] [Latin] Innocento, Episcopo Romæ [Latin] Dilecto Fratri Joanni Innocentius [Graecum] [Latin] Innocentius Eiscopus [Graecum] [Latin] Exemplum sacræ Honorii Augusti Ad Episcopos [Graecum] [Latin] Admonitio in Epistolas Sancti Joannis Chrysostom Dominæ Meæ [Graecum] [Latin] Ad eamdem Epist. …”
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Tabla de Contenidos: “…[Latin] [Graecum] Monitum in Alteram Orationem antiquam iret in Exsilium Cum iret in Exsilium [Latin] [Graecum] Post Reditum a priore Exsilio Ejusdem post Reditum [Latin] [Graecum] In Dimissionem Chananææ [Graecum] [Latin] In librum, quod Nemo Lædatur nisi a Seipso - Admonitio Liber [Latin] [Graecum] In librum ad eos qui scandalizati sunt ob adversitates - admonitio Ejusdem Liber [Latin] [Graecum] Monitum in Epistolas duas Joannis Chrysostomi ad Innoventium Papam Innocentio Episcopo Romæ [Graecum] [Latin] Innocento, Episcopo Romæ [Latin] Dilecto Fratri Joanni Innocentius [Graecum] [Latin] Innocentius Eiscopus [Graecum] [Latin] Exemplum sacræ Honorii Augusti Ad Episcopos [Graecum] [Latin] Admonitio in Epistolas Sancti Joannis Chrysostom Dominæ Meæ [Graecum] [Latin] Ad eamdem Epist. …”
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Tabla de Contenidos: “…Marcianum et Martyrium et in S. Andreæ ædem.Index Prior.Index Posterio…”
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Tabla de Contenidos: “…Introduction to this handbook / Rahman Azari, Alice Moncaster -- Minimising embodied carbon : a question of politics not percentages / Alice Moncaster -- Climate neutral and circular built environment : right here, right now / Guillaume Habert -- Net zero in buildings and construction : use and misuse of carbon offsets / Barnardino D'Amico, Francecso Pomponi -- Characterization of links between embodied carbon and thermal mass / Matan Mayer, James Grinham -- Introduction to section 2 / Alice Moncaster, Rahman Azari -- Building decarbonization in North America / Rahman Azari -- Embodied carbon in building regulation : development and implementation in Finland, Sweden and Denmark / Freja Nygaard Rasmussen and Harpa Birgisdottir, Tove Malmqvist, Matti Kuttinen, Tarja Hakkinen -- Global carbon budgets for the built environment : how far are we to achieve a 1.5°C limit in global warming? A Swiss example / Priore Yasmine, Guillaume Habert, Thomas Jusselme -- The levels process and the life levels project : supporting the development of quality data / Borja Izaola -- Embodied carbon : knowledge building for industry / Aoife Houlihan Wiberg, Harpa Birgisdottir, Freja Nygaard Rasmussen, Tove Malmqvist, Alice Moncaster, Ben James -- Introduction to Section 3 / Rahman Azari, Alice Moncaster -- Approaches and system boundaries for urban carbon accounts / Klaus Hubacek, Yuli Shan, Shaoqing Chen -- Quantifying the sunk carbon costs of cities : a case-study of 50 years of construction in Odense, Denmark / Srinivasa Gummidi, Benjamin Goldstein, Maud Lanau, Gang Liu, Joshua Sohn, Morten Birkved -- Embodied carbon in urban transport : what is the best way to decarbonise? …”

Tabla de Contenidos: “…-- Modularising VET programmes -- Modularisation can be beneficial to adults, employers and VET providers -- Modularisation in VET can be challenging -- Microcredentials can make modularisation more effective -- Recognising and validating prior learning -- Recognition of prior learning can make VET more accessible…”

Tabla de Contenidos: “…Convento de San Marcos (Leon). Señor, El Prior, y Convento de San Marcos de Leon ... ŕ los Reales pies de V. …”

Tabla de Contenidos: “…Case study 3: monthly data -- Case study 4: quarterly data -- Case study 5: annual data -- 2.3 - Missing Data, Solutions, and Transformations -- 2.3.1 - Variable transformation into logs and first differences -- 2.3.2 - Panel data estimations -- 2.3.3 - Interpretation of the cointegration equation -- 2.4 - Principal Component Analysis as a Method of the Variable Number Reduction -- 3 - Part 2: Variable Selection With Bayesian Analysis -- 3.1 - Introduction to Bayesian Inference -- 3.1.1 - Prior information, data, and posterior inference -- 3.1.2 - Literature review: Bayesian statistics in the EGN context -- 3.2 - Bayesian Estimation and Prediction -- 3.2.1 - Bayesian estimation, credible intervals, and its interpretation -- 3.2.2 - Posterior predictive inference -- 3.2.3 - Hypothesis testing -- 3.2.4 - Bayesian Hypothesis testing and Bayes factors -- 3.2.5 - An extension of hypothesis testing -- 3.2.5.1 - Model selection -- 3.2.6 - A particular problem: variable selection -- 3.2.7 - The robust prior -- 3.2.8 - Prior over the model space -- 3.2.9 - Posterior inferences in variable selection -- 3.2.10 - BayesVarSel an R package for Bayesian Variable Selection -- 3.3 - Selecting Influential Variables in the EGN -- 3.3.1 - Data and sources -- 3.3.2 - Model and variable selection -- 3.3.3 - Results -- 3.3.3.1 - Aggregate growth results -- 4 - Concluding Remarks -- 4.1 - Part 1 -- 4.2 - Part 2 -- References -- Further Readings -- Chapter 7 - Current Issues in Time-Series Analysis for the Energy-Growth Nexus (EGN) -- Asymmetries and Nonlinearities Case S... -- 1 - Introduction -- 1.1 - The EGN in Pakistan -- 2 - Literature Review -- 2.1 - The Up-to-Date Evolution of Bivariate Analysis in the EGN -- 2.2 - The Evolution of the Multivariate Framework in the EGN -- 3 - The Modeling, Data, and Methodology…”

Tabla de Contenidos: “…239 8.4 Bayesian Model Selection 274 8.5 SMC Samplers Estimators of Model Evidence 276 8.6 Multiple Risk Dependence Structure Model Selection: Copula Choice 277 9 Flexible Parametric Severity Models: Basics 289 9.1 Motivation for Flexible Parametric Severity Loss Models 289 9.2 Context of Flexible Heavy Tailed Loss Models in OpRisk and Insurance LDA Models 290 9.3 Empirical Analysis Justifying Heavy Tailed Loss Models in OpRisk 292 9.4 Flexible Distributions for Severity Models in OpRisk 294 9.5 Quantile Function Heavy Tailed Severity Models 294 9.6 Generalized Beta Family of Heavy Tailed Severity Models 321 9.7 Generalized Hyperbolic Families of Heavy Tailed Severity Models 328 9.8 Halphen Family of Flexible Severity Models: GIG and Hyperbolic 338 10 Modelling Dependence 353 10.1 Dependence Modelling Within and Between LDA Model Structures 353 10.2 General Notions of Dependence 358 10.3 Dependence Measures and Tail Dependence 364 10.4 Introduction to Parametric Dependence Modeling Through a Copula 380 10.5 Copula Model Families for OpRisk 387 10.6 Copula Parameter Estimation in Two Stages: Inference For the Margins 416 10.7 Multiple Risk LDA Compound Poisson Processes and Levy Copula 420 10.8 Multiple Risk LDA: Dependence Between Frequencies via Copula 425 10.9 Multiple Risk LDA: Dependence Between the k-th Event Times/Losses 425 10.10 Multiple Risk LDA: Dependence Between Aggregated Losses via Copula 430 10.11 Multiple Risk LDA: Structural Model with Common Factors 432 10.12 Multiple Risk LDA: Stochastic and Dependent Risk Profiles 434 10.13 Multiple Risk LDA: Dependence and Combining Different Data Sources 437 10.14 A Note on Negative Diversification and Dependence Modelling 445 11 Loss Aggregation 447 11.1 Introduction 447 11.2 Analytic Solution 448 11.3 Monte Carlo Method 454 11.4 Panjer Recursion 457 11.5 Panjer Extensions 462 11.6 Fast Fourier Transform 463 11.7 Closed-Form Approximation 466 11.8 Capital Charge Under Parameter Uncertainty 471 12 Scenario Analysis 477 12.1 Introduction 477 12.2 Examples of Expert Judgements 480 12.3 Pure Bayesian Approach (Estimating Prior) 482 12.4 Expert Distribution and Scenario Elicitation: learning from Bayesian methods 484 12.5 Building Models for Elicited Opinions: Heirarchical Dirichlet Models 487 12.6 Worst Case Scenario Framework 489 12.7 Stress Test Scenario Analysis 492 12.8 Bow-Tie Diagram 495 12.9 Bayesian Networks 497 12.10 Discussion 504 13 Combining Different Data Sources 507 13.1 Minimum variance principle 508 13.2 Bayesian Method to Combine Two Data Sources 510 13.3 Estimation of the Prior Using Data 528 13.4 Combining Expert Opinions with External and Internal Data 530 13.5 Combining Data Sources Using Credibility Theory 546 13.6 Nonparametric Bayesian approach via Dirichlet process 556 13.7 Combining using Dempster-Shafer structures and p-boxes 558 13.8 General Remarks 567 14 Multifactor Modelling and Regression for Loss Processes 571 14.1 Generalized Linear Model Regressions and the Exponential Family 571 14.2 Maximum Likelihood Estimation for Generalized Linear Models 573 14.3 Bayesian Generalized Linear Model Regressions and Regularization Priors 576 14.4 Bayesian Estimation and Model Selection via SMC Samplers 583 14.5 Illustrations of SMC Samplers Model Estimation and Selection for Bayesian GLM Regressions 585 14.6 Introduction to Quantile Regression Methods for OpRisk 590 14.7 Factor Modelling for Industry Data 597 14.8 Multifactor Modelling under EVT Approach 599 15 Insurance and Risk Transfer: Products and Modelling 601 15.1 Motivation for Insurance and Risk Transfer in OpRisk 602 15.2 Fundamentals on Insurance Product Structures for OpRisk 604 15.3 Single Peril Policy Products for OpRisk 609 15.4 Generic Insurance Product Structures for OpRisk 611 15.5 Closed Form LDA Models with Insurance Mitigations 621 16 Insurance and Risk Transfer: Pricing 663 16.1 Insurance Linked Securities and Catastrophe Bonds for OpRisk 664 16.2 Basics of Valuation of Insurance Linked Securities and Catastrophe Bonds for OpRisk 679 16.3 Applications of Pricing Insurance Linked Securities and Catastrophe Bonds 709 16.4 Sidecars, Multiple Peril Baskets and Umbrellas for OpRisk 726 16.5 Optimal Insurance Purchase Strategies for OpRisk Insurance via Multiple Optimal Stopping Times 733 A. …”

Tabla de Contenidos: “…5.7.2 Minimum MSE Equivariant Estimators -- 5.7.3 Minimum Risk Equivariant Estimators -- 5.7.4 The Pitman Estimators -- 5.8 ESTIMATING EQUATIONS -- 5.8.1 Moment-Equations Estimators -- 5.8.2 General Theory of Estimating Functions -- 5.9 PRETEST ESTIMATORS -- 5.10 ROBUST ESTIMATION OF THE LOCATION AND SCALE PARAMETERS OF SYMMETRIC DISTRIBUTIONS -- PART II: EXAMPLES -- PART III: PROBLEMS -- PART IV: SOLUTIONS OF SELECTED PROBLEMS -- 6 Confidence and Tolerance Intervals -- PART I: THEORY -- 6.1 GENERAL INTRODUCTION -- 6.2 THE CONSTRUCTION OF CONFIDENCE INTERVALS -- 6.3 OPTIMAL CONFIDENCE INTERVALS -- 6.4 TOLERANCE INTERVALS -- 6.5 DISTRIBUTION FREE CONFIDENCE AND TOLERANCE INTERVALS -- 6.6 SIMULTANEOUS CONFIDENCE INTERVALS -- 6.7 TWO-STAGE AND SEQUENTIAL SAMPLING FOR FIXED WIDTH CONFIDENCE INTERVALS -- PART II: EXAMPLES -- PART III: PROBLEMS -- PART IV: SOLUTION TO SELECTED PROBLEMS -- 7 Large Sample Theory for Estimation and Testing -- PART I: THEORY -- 7.1 CONSISTENCY OF ESTIMATORS AND TESTS -- 7.2 CONSISTENCY OF THE MLE -- 7.3 ASYMPTOTIC NORMALITY AND EFFICIENCY OF CONSISTENT ESTIMATORS -- 7.4 SECOND-ORDER EFFICIENCY OF BAN ESTIMATORS -- 7.5 LARGE SAMPLE CONFIDENCE INTERVALS -- 7.6 EDGEWORTH AND SADDLEPOINT APPROXIMATIONS TO THE DISTRIBUTION OF THE MLE: ONE-PARAMETER CANONICAL EXPONENTIAL FAMILIES -- 7.7 LARGE SAMPLE TESTS -- 7.8 PITMAN'S ASYMPTOTIC EFFICIENCY OF TESTS -- 7.9 ASYMPTOTIC PROPERTIES OF SAMPLE QUANTILES -- PART II: EXAMPLES -- PART III: PROBLEMS -- PART IV: SOLUTION OF SELECTED PROBLEMS -- 8 Bayesian Analysis in Testing and Estimation -- PART I: THEORY -- 8.1 THE BAYESIAN FRAMEWORK -- 8.1.1 Prior, Posterior, and Predictive Distributions -- 8.1.2 Noninformative and Improper Prior Distributions -- 8.1.3 Risk Functions and Bayes Procedures -- 8.2 BAYESIAN TESTING OF HYPOTHESIS -- 8.2.1 Testing Simple Hypothesis…”

“…"The Third Edition retains the general organization of the prior two editions, but it incorporates new material throughout the text. …”
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“…It is primarily aimed at postgraduate and undergraduate students with prior knowledge in functional analysis and operator theory. …”
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“…It focuses on teaching arpeggio techniques without requiring prior knowledge of musical notation. The guide provides step-by-step instructions on various finger placements and techniques, such as finger substitution and simultaneous attacks. …”

“…While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product. …”

“…This practical desk companion doubles as a comprehensive overview of the basic knowledge and skills needed by CCNA and CCNP exam takers. Prior familiarity with Cisco routing and switching is desirable but not necessary, as Chris Carthern, Dr. …”
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“…Preface to the Third Edition The chemical makeup of a collected water sample reflects the history of its prior flow path, particularly the minerals it has contacted, its contact time with these minerals, and the values of temperature, pH, and redox potential along the flow path. …”

“…The conference made clear that important information on Indigenous cultural heritage has remained unexplored or has not been adequately linked with specific actors (such as WIPO) or specific issues (such as free, prior and informed consent). Indigenous leaders explained the impact that disrespect of their cultural heritage has had on their identity, well-being and development. …”