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[null,"1.","Record Nr.",null,"UNINA9910437962503321"]
[null,null,"Titolo",null,"Handbook of assessing variants and complications in anxiety disorders / / Dean McKay, Eric A. Storch, editors"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Springer, c2013"]
[null,null,"ISBN",null,"1-4614-6452-8"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (255 p.)"]
[null,null,"Disciplina",null,"150"]
[{"$nulls":4},"155.4"]
[{"$nulls":4},"155424"]
[{"$nulls":4},"616.85/2206"]
[null,null,"Soggetti",null,"Anxiety - Testing"]
[{"$nulls":4},"Anxiety disorders"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Section I: Complexities in Assessment of Primary Anxiety Conditions -- Chapter 1: Assessment of Social and Generalized Anxiety Disorder -- Chapter 2: Assessment and Treatment of Deficits in Social Skills Functioning and Social Anxiety In Children Engaging in School Refusal Behaviors -- Chapter 3: Assessment of Selective Mutism and School Refusal Behavior -- Chapter 4: Neuropsychological Assessment of Obsessive-Compulsive Disorder -- Chapter 5: Assessment of Tics and Comorbid Obsessive-Compulsive Symptoms -- Chapter 6: Intelligence Testing and Treatment Planning with Children -- Section II: Complexities in Assessment of Personality and Behavioral Disturbance Associated with Anxiety Conditions -- Chapter 7: Assessment of Substance Abuse and Dependence in Anxiety Disorders -- Chapter 8: Functional Assessment of Comorbid and Secondary Disorders: Identifying Conditions for Primary Treatment -- Chapter 9: Assessment of Suicidal and Non-Suicidal Self-Injury in Anxiety Disorders -- Chapter 10: Assessment of Anxiety Symptoms Using the MMPI-2, MMPI-2-RF, and MMPI-A -- Chapter 11: Anxiety Disorders & Evidence-Based Practice: The Role of Broadband Self-Report Measures of Personality in Diagnosis, Case Conceptualization & Treatment Planning -- Chapter 12: Contemporary Personality Disorder Assessment in Clients with Anxiety Disorders -- Chapter 13: Projective Personality Assessment of Anxiety: A Critical Appraisal -- Chapter 14: Assessment of Insight and "]
[{"$nulls":4},"Overvalued Ideation in Obsessive-Compulsive Disorder -- Chapter 15: Assessment of Disruptive Behavior Disorders in Anxiety -- Chapter 16: Assessing Complexities in Anxiety Disorders: Consideration of Future Directions."]
[null,null,null,"Sommario/riassunto","The Handbook of Assessing Variants and Complications in Anxiety Disorders assembles current findings on assessment methods and applies them to common complicating factors, including comorbid personality and behavioral problems. Chapters examine innovative approaches to assessment of anxiety in children and adults, provide leading insights into timely topics (e.g., school refusal, self-injurious behaviors), and analyze strengths and weaknesses of widely used assessment tools. In clarifying the assessment process, contributors give readers a clear perspective on choosing treatment options in keeping with the trend toward targeted, evidence-based practice, and pinpoint needs for further research. The Handbook's coverage spans the anxiety spectrum, including areas such as: Assessment of social and generalized anxiety disorder. Neuropsychological assessment of obsessive-compulsive disorder.­ Intelligence testing and treatment planning with children. Assessment of substance abuse and dependence in anxiety disorders. Personality disorder assessment in clients with anxiety disorders. Functional assessment of comorbid and secondary disorders: identifying conditions for primary treatment. The Handbook of Assessing Variants and Complications in Anxiety Disorders is an essential reference for researchers, scientist-practitioners, and graduate students in clinical child, school, and developmental psychology; social work; psychiatry; psychotherapy; counseling; and pediatrics. And its companion volume, the Handbook of Treating Variants and Complications in Anxiety Disorders, further explores these findings in the context of the next stage of care."]
[null,"2.","Record Nr.",null,"UNINA9910741172203321"]
[null,null,"Autore",null,"Marwala Tshilidzi <1971->"]
[null,null,"Titolo",null,"Economic modeling using artificial intelligence methods / / Tshilidzi Marwala"]
[null,null,"Pubbl/distr/stampa",null,"London, : Springer, 2013"]
[null,null,"ISBN",null,"1-4471-5010-4"]
[null,null,"Edizione",null,"[1st ed. 2013.]"]
[null,null,"Descrizione fisica",null,"1 online resource (xvi, 261 pages) : illustrations (some color)"]
[null,null,"Collana",null,"Advanced Information and Knowledge Processing, , 1610-3947"]
[null,null,"Disciplina",null,"330.0113"]
[null,null,"Soggetti",null,"Econometric models"]
[{"$nulls":4},"Artificial intelligence - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"ISSN: 1610-3947.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Foreword -- Preface -- Acknowledgements -- Introduction to Economic Modeling -- Techniques for Economic Modeling: Unlocking the Character of Data -- Automatic Relevance Determination in Economic Modeling -- Neural Approaches to Economic Modeling -- Bayesian Support Vector Machines for Economic Modeling: Application to Option Pricing -- Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data -- Missing Data Approaches to Economic Modeling: Optimization Approach -- Correlations versus Causality Approaches to Economic Modeling -- Evolutionary Approaches to Computational Economics: Application to Portfolio Optimization -- Real-time Approaches to Computational Economics: Self Adaptive Economic Systems -- Multi-Agent Approaches to Economic Modeling: Game Theory, Ensembles, Evolution and the Stock Market -- Control Approaches to Economic Modeling: Application to Inflation Targeting -- Modeling Interstate Conflict: The Role of Economic Interdependency for Maintaining Peace -- Conclusions and Further Work -- Index."]
[null,null,null,"Sommario/riassunto","Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data. Traditionally, economic modeling has been modeled in the linear domain where the principles of superposition are valid. The application of artificial intelligence for economic modeling allows for a flexible multi-order non-linear modeling. In addition, game theory has largely been applied in economic modeling. However, the inherent limitation of game theory when dealing with many player games encourages the use "]
[{"$nulls":4},"of multi-agent systems for modeling economic phenomena. The artificial intelligence techniques used to model economic data include: multi-layer perceptron neural networks radial basis functions support vector machines rough sets genetic algorithm particle swarm optimization simulated annealing multi-agent system incremental learning fuzzy networks Signal processing techniques are explored to analyze economic data, and these techniques are the time domain methods, time-frequency domain methods and fractals dimension approaches. Interesting economic problems such as causality versus correlation, simulating the stock market, modeling and controling inflation, option pricing, modeling economic growth as well as portfolio optimization are examined. The relationship between economic dependency and interstate conflict is explored, and knowledge on how economics is useful to foster peace – and vice versa – is investigated. Economic Modeling Using Artificial Intelligence Methods deals with the issue of causality in the non-linear domain and applies the automatic relevance determination, the evidence framework, Bayesian approach and Granger causality to understand causality and correlation. Economic Modeling Using Artificial Intelligence Methods makes an important contribution to the area of econometrics, and is a valuable source of reference for graduate students, researchers and financial practitioners."]