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Advances in Robust Fractional Control / / by Fabrizio Padula, Antonio Visioli
| Advances in Robust Fractional Control / / by Fabrizio Padula, Antonio Visioli |
| Autore | Padula Fabrizio |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (182 p.) |
| Disciplina |
519.5/3
629.8 |
| Soggetto topico |
Control engineering
Chemical engineering Industrial engineering Production engineering Control and Systems Theory Industrial Chemistry/Chemical Engineering Industrial and Production Engineering |
| ISBN | 3-319-10930-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to Fractional Calculus -- Fractional Systems for Control -- Fractional Proportional-Integral-Derivative Controllers -- FOPID Controller Additional Functionalities.- H-infinity Control of Fractional Systems -- H-infinity Optimization-based FOPID Design -- Control Design Based on Input-Output Inversion. |
| Record Nr. | UNINA-9910299845803321 |
Padula Fabrizio
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied longitudinal analysis / / Garrett M. Fitzmaurice, Nan M. Laird, James H. Ware
| Applied longitudinal analysis / / Garrett M. Fitzmaurice, Nan M. Laird, James H. Ware |
| Autore | Fitzmaurice Garrett M. <1962-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2011] |
| Descrizione fisica | 1 online resource (1309 p.) |
| Disciplina |
519.5/3
519.53 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Longitudinal method
Regression analysis Multivariate analysis Medical statistics |
| ISBN |
9781119513469
1-119-51346-4 1-118-55179-6 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Half Title page; Title page; Copyright page; Dedication; Preface; Preface to First Edition; Acknowledgments; Part I: Introduction to Longitudinal and Clustered Data; Chapter 1: Longitudinal and Clustered Data; 1.1 Introduction; 1.2 Longitudinal and Clustered Data; 1.3 Examples; 1.4 Regression Models for Correlated Responses; 1.5 Organization of the Book; 1.6 Further Reading; Chapter 2: Longitudinal Data: Basic Concepts; 2.1 Introduction; 2.2 Objectives of Longitudinal Analysis; 2.3 Defining Features of Longitudinal Data; 2.4 Example: Treatment of Lead-Exposed Children Trial
2.5 Sources of Correlation in Longitudinal Data2.6 Further Reading; Part II: Linear Models for Longitudinal Continuous Data; Chapter 3: Overview of Linear Models for Longitudinal Data; 3.1 Introduction; 3.2 Notation and Distributional Assumptions; 3.3 Simple Descriptive Methods of Analysis; 3.4 Modeling the Mean; 3.5 Modeling the Covariance; 3.6 Historical Approaches; 3.7 Further Reading; Chapter 4: Estimation and Statistical Inference; 4.1 Introduction; 4.2 Estimation: Maximum Likelihood; 4.3 Missing Data Issues; 4.4 Statistical Inference; 4.5 Restricted Maximum Likelihood (REML) Estimation 4.6 Further ReadingChapter 5: Modeling the Mean: Analyzing Response Profiles; 5.1 Introduction; 5.2 Hypotheses Concerning Response Profiles; 5.3 General Linear Model Formulation; 5.4 Case Study; 5.5 One-Degree-of-Freedom Tests for Group by Time Interaction; 5.6 Adjustment for Baseline Response; 5.7 Alternative Methods of Adjusting for Baseline Response; 5.8 Strengths and Weaknesses of Analyzing Response Profiles; 5.9 Computing: Analyzing Response Profiles Using PROC MIXED in SAS; 5.10 Further Reading; Chapter 6: Modeling the Mean: Parametric Curves; 6.1 Introduction 6.2 Polynomial Trends in Time6.3 Linear Splines; 6.4 General Linear Model Formulation; 6.5 Case Studies; 6.6 Computing: Fitting Parametric Curves Using PROC MIXED in SAS; 6.7 Further Reading; Chapter 7: Modeling the Covariance; 7.1 Introduction; 7.2 Implications of Correlation among Longitudinal Data; 7.3 Unstructured Covariance; 7.4 Covariance Pattern Models; 7.5 Choice among Covariance Pattern Models; 7.6 Case Study; 7.7 Discussion: Strengths and Weaknesses of Covariance Pattern Models; 7.8 Computing: Fitting Covariance Pattern Models Using PROC MIXED in SAS; 7.9 Further Reading Chapter 8: Linear Mixed Effects Models8.1 Introduction; 8.2 Linear Mixed Effects Models; 8.3 Random Effects Covariance Structure; 8.4 Two-Stage Random Effects Formulation; 8.5 Choice among Random Effects Covariance Models; 8.6 Prediction of Random Effects; 8.7 Prediction and Shrinkage; 8.8 Case Studies; 8.9 Computing: Fitting Linear Mixed Effects Models Using PROC MIXED in SAS; 8.10 Further Reading; Chapter 9: Fixed Effects versus Random Effects Models; 9.1 Introduction; 9.2 Linear Fixed Effects Models; 9.3 Fixed Effects versus Random Effects: Bias-Variance Trade-off 9.4 Resolving the Dilemma of Choosing Between Fixed and Random Effects Models |
| Record Nr. | UNINA-9910555092603321 |
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Fitzmaurice Garrett M. <1962->
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| Hoboken, New Jersey : , : Wiley, , [2011] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied longitudinal analysis / / Garrett M. Fitzmaurice, Nan M. Laird, James H. Ware
| Applied longitudinal analysis / / Garrett M. Fitzmaurice, Nan M. Laird, James H. Ware |
| Autore | Fitzmaurice Garrett M. <1962-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2011] |
| Descrizione fisica | 1 online resource (1309 p.) |
| Disciplina |
519.5/3
519.53 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Longitudinal method
Regression analysis Multivariate analysis Medical statistics |
| ISBN |
1-119-51346-4
1-118-55179-6 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Half Title page; Title page; Copyright page; Dedication; Preface; Preface to First Edition; Acknowledgments; Part I: Introduction to Longitudinal and Clustered Data; Chapter 1: Longitudinal and Clustered Data; 1.1 Introduction; 1.2 Longitudinal and Clustered Data; 1.3 Examples; 1.4 Regression Models for Correlated Responses; 1.5 Organization of the Book; 1.6 Further Reading; Chapter 2: Longitudinal Data: Basic Concepts; 2.1 Introduction; 2.2 Objectives of Longitudinal Analysis; 2.3 Defining Features of Longitudinal Data; 2.4 Example: Treatment of Lead-Exposed Children Trial
2.5 Sources of Correlation in Longitudinal Data2.6 Further Reading; Part II: Linear Models for Longitudinal Continuous Data; Chapter 3: Overview of Linear Models for Longitudinal Data; 3.1 Introduction; 3.2 Notation and Distributional Assumptions; 3.3 Simple Descriptive Methods of Analysis; 3.4 Modeling the Mean; 3.5 Modeling the Covariance; 3.6 Historical Approaches; 3.7 Further Reading; Chapter 4: Estimation and Statistical Inference; 4.1 Introduction; 4.2 Estimation: Maximum Likelihood; 4.3 Missing Data Issues; 4.4 Statistical Inference; 4.5 Restricted Maximum Likelihood (REML) Estimation 4.6 Further ReadingChapter 5: Modeling the Mean: Analyzing Response Profiles; 5.1 Introduction; 5.2 Hypotheses Concerning Response Profiles; 5.3 General Linear Model Formulation; 5.4 Case Study; 5.5 One-Degree-of-Freedom Tests for Group by Time Interaction; 5.6 Adjustment for Baseline Response; 5.7 Alternative Methods of Adjusting for Baseline Response; 5.8 Strengths and Weaknesses of Analyzing Response Profiles; 5.9 Computing: Analyzing Response Profiles Using PROC MIXED in SAS; 5.10 Further Reading; Chapter 6: Modeling the Mean: Parametric Curves; 6.1 Introduction 6.2 Polynomial Trends in Time6.3 Linear Splines; 6.4 General Linear Model Formulation; 6.5 Case Studies; 6.6 Computing: Fitting Parametric Curves Using PROC MIXED in SAS; 6.7 Further Reading; Chapter 7: Modeling the Covariance; 7.1 Introduction; 7.2 Implications of Correlation among Longitudinal Data; 7.3 Unstructured Covariance; 7.4 Covariance Pattern Models; 7.5 Choice among Covariance Pattern Models; 7.6 Case Study; 7.7 Discussion: Strengths and Weaknesses of Covariance Pattern Models; 7.8 Computing: Fitting Covariance Pattern Models Using PROC MIXED in SAS; 7.9 Further Reading Chapter 8: Linear Mixed Effects Models8.1 Introduction; 8.2 Linear Mixed Effects Models; 8.3 Random Effects Covariance Structure; 8.4 Two-Stage Random Effects Formulation; 8.5 Choice among Random Effects Covariance Models; 8.6 Prediction of Random Effects; 8.7 Prediction and Shrinkage; 8.8 Case Studies; 8.9 Computing: Fitting Linear Mixed Effects Models Using PROC MIXED in SAS; 8.10 Further Reading; Chapter 9: Fixed Effects versus Random Effects Models; 9.1 Introduction; 9.2 Linear Fixed Effects Models; 9.3 Fixed Effects versus Random Effects: Bias-Variance Trade-off 9.4 Resolving the Dilemma of Choosing Between Fixed and Random Effects Models |
| Record Nr. | UNINA-9910830134903321 |
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Fitzmaurice Garrett M. <1962->
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| Hoboken, New Jersey : , : Wiley, , [2011] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis
| Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis |
| Autore | Denis Daniel J. <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2016] |
| Descrizione fisica | 1 online resource (763 pages) : illustrations |
| Disciplina | 519.5/3 |
| Soggetto topico |
Analysis of variance
Multivariate analysis |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-118-63223-0
1-118-63231-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910460626803321 |
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Denis Daniel J. <1974->
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| Hoboken, New Jersey : , : Wiley, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis
| Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis |
| Autore | Denis Daniel J. <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2016] |
| Descrizione fisica | 1 online resource (763 pages) : illustrations |
| Disciplina | 519.5/3 |
| Soggetto topico |
Analysis of variance
Multivariate analysis |
| ISBN |
1118632230
9781118632239 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910796096703321 |
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Denis Daniel J. <1974->
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| Hoboken, New Jersey : , : Wiley, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis
| Applied univariate, bivariate, and multivariate statistics / / Daniel J. Denis |
| Autore | Denis Daniel J. <1974-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2016] |
| Descrizione fisica | 1 online resource (763 pages) : illustrations |
| Disciplina | 519.5/3 |
| Soggetto topico |
Analysis of variance
Multivariate analysis |
| ISBN |
1118632230
9781118632239 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910808575603321 |
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Denis Daniel J. <1974->
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| Hoboken, New Jersey : , : Wiley, , [2016] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song
| Basic and advanced Bayesian structural equation modeling [[electronic resource] ] : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song |
| Autore | Lee Sik-Yum |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2012 |
| Descrizione fisica | 1 online resource (397 p.) |
| Disciplina | 519.5/3 |
| Altri autori (Persone) | SongXin-Yuan |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-118-35887-2
1-280-87995-5 9786613721266 1-118-35880-5 1-118-35888-0 1-118-35943-7 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Basic and Advanced Bayesian Structural Equation Modeling; Contents; About the authors; Preface; 1 Introduction; 1.1 Observed and latent variables; 1.2 Structural equation model; 1.3 Objectives of the book; 1.4 The Bayesian approach; 1.5 Real data sets and notation; Appendix 1.1: Information on real data sets; References; 2 Basic concepts and applications of structural equation models; 2.1 Introduction; 2.2 Linear SEMs; 2.2.1 Measurement equation; 2.2.2 Structural equation and one extension; 2.2.3 Assumptions of linear SEMs; 2.2.4 Model identification; 2.2.5 Path diagram
2.3 SEMs with fixed covariates 2.3.1 The model; 2.3.2 An artificial example; 2.4 Nonlinear SEMs; 2.4.1 Basic nonlinear SEMs; 2.4.2 Nonlinear SEMs with fixed covariates; 2.4.3 Remarks; 2.5 Discussion and conclusions; References; 3 Bayesian methods for estimating structural equation models; 3.1 Introduction; 3.2 Basic concepts of the Bayesian estimation and prior distributions; 3.2.1 Prior distributions; 3.2.2 Conjugate prior distributions in Bayesian analyses of SEMs; 3.3 Posterior analysis using Markov chain Monte Carlo methods; 3.4 Application of Markov chain Monte Carlo methods 3.5 Bayesian estimation via WinBUGS Appendix 3.1: The gamma, inverted gamma, Wishart, and inverted Wishart distributions and their characteristics; Appendix 3.2: The Metropolis-Hastings algorithm; Appendix 3.3: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω]; Appendix 3.4: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω] in nonlinear SEMs with covariates; Appendix 3.5: WinBUGS code; Appendix 3.6: R2WinBUGS code; References; 4 Bayesian model comparison and model checking; 4.1 Introduction; 4.2 Bayes factor; 4.2.1 Path sampling; 4.2.2 A simulation study; 4.3 Other model comparison statistics 4.3.1 Bayesian information criterion and Akaike information criterion 4.3.2 Deviance information criterion; 4.3.3 Lν-measure; 4.4 Illustration; 4.5 Goodness of fit and model checking methods; 4.5.1 Posterior predictive p-value; 4.5.2 Residual analysis; Appendix 4.1: WinBUGS code; Appendix 4.2: R code in Bayes factor example; Appendix 4.3: Posterior predictive p-value for model assessment; References; 5 Practical structural equation models; 5.1 Introduction; 5.2 SEMs with continuous and ordered categorical variables; 5.2.1 Introduction; 5.2.2 The basic model; 5.2.3 Bayesian analysis 5.2.4 Application: Bayesian analysis of quality of life data 5.2.5 SEMs with dichotomous variables; 5.3 SEMs with variables from exponential family distributions; 5.3.1 Introduction; 5.3.2 The SEM framework with exponential family distributions; 5.3.3 Bayesian inference; 5.3.4 Simulation study; 5.4 SEMs with missing data; 5.4.1 Introduction; 5.4.2 SEMs with missing data that are MAR; 5.4.3 An illustrative example; 5.4.4 Nonlinear SEMs with nonignorable missing data; 5.4.5 An illustrative real example Appendix 5.1: Conditional distributions and implementation of the MH algorithm for SEMs with continuous and ordered categorical variables |
| Record Nr. | UNINA-9910141259703321 |
|
Lee Sik-Yum
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| Hoboken, : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Basic and advanced Bayesian structural equation modeling : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song
| Basic and advanced Bayesian structural equation modeling : with applications in the medical and behavioral sciences / / Sik-Yum Lee and Xin-Yuan Song |
| Autore | Lee Sik-Yum |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, : Wiley, 2012 |
| Descrizione fisica | 1 online resource (397 p.) |
| Disciplina | 519.5/3 |
| Altri autori (Persone) | SongXin-Yuan |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Structural equation modeling
Bayesian statistical decision theory |
| ISBN |
1-118-35887-2
1-280-87995-5 9786613721266 1-118-35880-5 1-118-35888-0 1-118-35943-7 |
| Classificazione | MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Basic and Advanced Bayesian Structural Equation Modeling; Contents; About the authors; Preface; 1 Introduction; 1.1 Observed and latent variables; 1.2 Structural equation model; 1.3 Objectives of the book; 1.4 The Bayesian approach; 1.5 Real data sets and notation; Appendix 1.1: Information on real data sets; References; 2 Basic concepts and applications of structural equation models; 2.1 Introduction; 2.2 Linear SEMs; 2.2.1 Measurement equation; 2.2.2 Structural equation and one extension; 2.2.3 Assumptions of linear SEMs; 2.2.4 Model identification; 2.2.5 Path diagram
2.3 SEMs with fixed covariates 2.3.1 The model; 2.3.2 An artificial example; 2.4 Nonlinear SEMs; 2.4.1 Basic nonlinear SEMs; 2.4.2 Nonlinear SEMs with fixed covariates; 2.4.3 Remarks; 2.5 Discussion and conclusions; References; 3 Bayesian methods for estimating structural equation models; 3.1 Introduction; 3.2 Basic concepts of the Bayesian estimation and prior distributions; 3.2.1 Prior distributions; 3.2.2 Conjugate prior distributions in Bayesian analyses of SEMs; 3.3 Posterior analysis using Markov chain Monte Carlo methods; 3.4 Application of Markov chain Monte Carlo methods 3.5 Bayesian estimation via WinBUGS Appendix 3.1: The gamma, inverted gamma, Wishart, and inverted Wishart distributions and their characteristics; Appendix 3.2: The Metropolis-Hastings algorithm; Appendix 3.3: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω]; Appendix 3.4: Conditional distributions [Ω|Y,θ] and [θ|Y,Ω] in nonlinear SEMs with covariates; Appendix 3.5: WinBUGS code; Appendix 3.6: R2WinBUGS code; References; 4 Bayesian model comparison and model checking; 4.1 Introduction; 4.2 Bayes factor; 4.2.1 Path sampling; 4.2.2 A simulation study; 4.3 Other model comparison statistics 4.3.1 Bayesian information criterion and Akaike information criterion 4.3.2 Deviance information criterion; 4.3.3 Lν-measure; 4.4 Illustration; 4.5 Goodness of fit and model checking methods; 4.5.1 Posterior predictive p-value; 4.5.2 Residual analysis; Appendix 4.1: WinBUGS code; Appendix 4.2: R code in Bayes factor example; Appendix 4.3: Posterior predictive p-value for model assessment; References; 5 Practical structural equation models; 5.1 Introduction; 5.2 SEMs with continuous and ordered categorical variables; 5.2.1 Introduction; 5.2.2 The basic model; 5.2.3 Bayesian analysis 5.2.4 Application: Bayesian analysis of quality of life data 5.2.5 SEMs with dichotomous variables; 5.3 SEMs with variables from exponential family distributions; 5.3.1 Introduction; 5.3.2 The SEM framework with exponential family distributions; 5.3.3 Bayesian inference; 5.3.4 Simulation study; 5.4 SEMs with missing data; 5.4.1 Introduction; 5.4.2 SEMs with missing data that are MAR; 5.4.3 An illustrative example; 5.4.4 Nonlinear SEMs with nonignorable missing data; 5.4.5 An illustrative real example Appendix 5.1: Conditional distributions and implementation of the MH algorithm for SEMs with continuous and ordered categorical variables |
| Record Nr. | UNINA-9910821778903321 |
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Lee Sik-Yum
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| Hoboken, : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cluster analysis / / Brian S. Everitt ... [et al.]
| Cluster analysis / / Brian S. Everitt ... [et al.] |
| Edizione | [5th ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2011 |
| Descrizione fisica | 1 online resource (xii, 330 pages) : illustrations |
| Disciplina | 519.5/3 |
| Altri autori (Persone) | EverittBrian |
| Collana | Wiley series in probability and statistics |
| Soggetto topico | Cluster analysis |
| ISBN |
1-280-76795-2
9786613678720 1-118-30300-8 0-470-97781-7 0-470-97780-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Matter -- An Introduction to Classification and Clustering -- Detecting Clusters Graphically -- Measurement of Proximity -- Hierarchical Clustering -- Optimization Clustering Techniques -- Finite Mixture Densities as Models for Cluster Analysis -- Model-Based Cluster Analysis for Structured Data -- Miscellaneous Clustering Methods -- Some Final Comments and Guidelines -- Bibliography -- Index. |
| Record Nr. | UNINA-9910140852403321 |
| Hoboken, N.J., : Wiley, 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cluster effects in mining complex data [[electronic resource] /] / M. Ishaq Bhati
| Cluster effects in mining complex data [[electronic resource] /] / M. Ishaq Bhati |
| Autore | Bhatti M. Ishaq |
| Pubbl/distr/stampa | New York, : Nova Science Publisher's, c2012 |
| Descrizione fisica | 1 online resource (267 p.) |
| Disciplina | 519.5/3 |
| Collana | Mathematics research developments |
| Soggetto topico |
Cluster analysis
Data mining Econometrics |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-62808-669-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910462368403321 |
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Bhatti M. Ishaq
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| New York, : Nova Science Publisher's, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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