Computational modeling in cognition principles and practice / Stephan Lewandowsky and Simon Farrell.
A clear introduction to the principles of using computational and mathematical models in psychology and cognitive science.
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Full Text (via SAGE) |
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| Format: | eBook |
| Language: | English |
| Published: |
Thousand Oaks :
SAGE Publications,
2010.
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| Subjects: |
MARC
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| 100 | 1 | |a Lewandowsky, Stephan. | |
| 245 | 1 | 0 | |a Computational modeling in cognition |b principles and practice / |c Stephan Lewandowsky and Simon Farrell. |
| 260 | |a Thousand Oaks : |b SAGE Publications, |c 2010. | ||
| 300 | |a 1 online resource (327 p.) | ||
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| 505 | 0 | |a Cover Page -- Title Page -- Copyright -- Contents -- Preface -- 1. Introduction -- 1.1 Models and Theories in Science -- 1.2 Why Quantitative Modeling? -- 1.3 Quantitative Modeling in Cognition -- 1.3.1 Models and Data -- 1.3.2 From Ideas to Models -- 1.3.3 Summary -- 1.4 The Ideas Underlying Modeling and Its Distinct Applications -- 1.4.1 Elements of Models -- 1.4.2 Data Description -- 1.4.3 Process Characterization -- 1.4.4 Process Explanation -- 1.4.5 Classes of Models -- 1.5 What Can We Expect From Models? -- 1.5.1 Classification of Phenomena -- 1.5.2 Emergence of Understanding. | |
| 505 | 8 | |a 1.5.3 Exploration of Implications -- 1.6 Potential Problems -- 1.6.1 Scope and Testability -- 1.6.2 Identification and Truth -- 2. From Words to Models: Building a Toolkit -- 2.1 Working Memory -- 2.1.1 The Phonological Loop -- 2.1.2 Theoretical Accounts of the Word Length Effect -- 2.2 The Phonological Loop: 144 Models of Working Memory -- 2.2.1 Decay Process -- 2.2.2 Recall Process -- 2.2.3 Rehearsal -- 2.3 Building a Simulation -- 2.3.1 MATLAB -- 2.3.2 The Target Methodology -- 2.3.3 Setting Up the Simulation -- 2.3.4 Some Unanticipated Results -- 2.3.5 Variability in Decay. | |
| 505 | 8 | |a 2.4 What Can We Learn From These Simulations? -- 2.4.1 The Phonological Loop Model Instantiated -- 2.4.2 Testability and Falsifiability -- 2.4.3 Revisiting Model Design: Foundational Decisions -- 2.5 The Basic Toolkit -- 2.5.1 Parameters -- 2.5.2 Discrepancy Function -- 2.5.3 Parameter Estimation and Model-Fitting Techniques -- 2.6 Models and Data: Sufficiency and Explanation -- 2.6.1 Sufficiency of a Model -- 2.6.2 Verisimilitude Versus Truth -- 2.6.3 The Nature of Explanations -- 3. Basic Parameter Estimation Techniques -- 3.1 Fitting Models to Data: Parameter Estimation. | |
| 505 | 8 | |a 3.1.1 Visualizing Modeling -- 3.1.2 An Example -- 3.1.3 Inside the Box: Parameter Estimation Techniques -- 3.2 Considering the Data: What Level of Analysis? -- 3.2.1 Implications of Averaging -- 3.2.2 Fitting Individual Participants -- 3.2.3 Fitting Subgroups of Data -- 3.2.4 Fitting Aggregate Data -- 3.2.5 Having Your Cake and Eating It: Multilevel Modeling -- 3.2.6 Recommendations -- 4. Maximum Likelihood Estimation -- 4.1 Basics of Probabilities -- 4.1.1 Defining Probability -- 4.1.2 Properties of Probabilities -- 4.1.3 Probability Functions -- 4.2 What Is a Likelihood? | |
| 505 | 8 | |a 4.2.1 Inverse Probability and Likelihood -- 4.3 Defining a Probability Function -- 4.3.1 Probability Functions Specified by the Psychological Model -- 4.3.2 Probability Functions via Data Models -- 4.3.3 Two Types of Probability Functions -- 4.3.4 Extending the Data Model -- 4.3.5 Extension to Multiple Data Points and Multiple Parameters -- 4.4 Finding the Maximum Likelihood -- 4.5 Maximum Likelihood Estimation for Multiple Participants -- 4.5.1 Estimation for Individual Participants -- 4.5.2 Estimating a Single Set of Parameters -- 4.6 Properties of Maximum Likelihood Estimators. | |
| 500 | |a 5. Parameter Uncertainty and Model Comparison. | ||
| 520 | 8 | |a A clear introduction to the principles of using computational and mathematical models in psychology and cognitive science. | |
| 650 | 0 | |a Cognition |x Mathematical models. | |
| 650 | 7 | |a Cognition |x Mathematical models. |2 fast |0 (OCoLC)fst00866468 | |
| 700 | 1 | |a Farrell, Simon, |d 1976- |1 https://id.oclc.org/worldcat/entity/E39PBJbM6vGqpHTKXYKYT8vrbd | |
| 758 | |i has work: |a Computational modeling in cognition (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFHJRfCjTkvbtPVgw9T7f3 |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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