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Applications of wavelet multiresolution analysis / / Silvia Alejandra Seminara, Juan Pablo Muszkats, María Inés Troparevsky, editors
| Applications of wavelet multiresolution analysis / / Silvia Alejandra Seminara, Juan Pablo Muszkats, María Inés Troparevsky, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XII, 88 p. 46 illus., 36 illus. in color.) |
| Disciplina | 510 |
| Collana | ICIAM 2019 SEMA SIMAI Springer Series |
| Soggetto topico |
Mathematics
Ondetes (Matemàtica) Anàlisi multivariable |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-61713-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Fabio, M. et al., Approximate Solutions to Fractional Boundary Value Problems by Wavelet Decomposition Methods -- Calderón, L., Wavelet B-splines bases on the interval for solving boundary value problems -- La Mura, G. et al, Kalman-Wavelet combined Filtering -- Arouxet, M. et al., Using the Wavelet Transform for Time Series Analysis -- Muszkats, J. et al., Application of Wavelet Transform to Damage Detection in Brittle Materials via Energy and Entropy Evaluation of Acoustic Emission Signals. |
| Record Nr. | UNISA-996466556903316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applications of wavelet multiresolution analysis / / Silvia Alejandra Seminara, Juan Pablo Muszkats, María Inés Troparevsky, editors
| Applications of wavelet multiresolution analysis / / Silvia Alejandra Seminara, Juan Pablo Muszkats, María Inés Troparevsky, editors |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XII, 88 p. 46 illus., 36 illus. in color.) |
| Disciplina | 510 |
| Collana | ICIAM 2019 SEMA SIMAI Springer Series |
| Soggetto topico |
Mathematics
Ondetes (Matemàtica) Anàlisi multivariable |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-61713-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Fabio, M. et al., Approximate Solutions to Fractional Boundary Value Problems by Wavelet Decomposition Methods -- Calderón, L., Wavelet B-splines bases on the interval for solving boundary value problems -- La Mura, G. et al, Kalman-Wavelet combined Filtering -- Arouxet, M. et al., Using the Wavelet Transform for Time Series Analysis -- Muszkats, J. et al., Application of Wavelet Transform to Damage Detection in Brittle Materials via Energy and Entropy Evaluation of Acoustic Emission Signals. |
| Record Nr. | UNINA-9910484210103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied logistic regression [[electronic resource] ] : David W. Hosmer, Stanley Lemeshow, Rodney X. Sturdivant
| Applied logistic regression [[electronic resource] ] : David W. Hosmer, Stanley Lemeshow, Rodney X. Sturdivant |
| Autore | Hosmer David W |
| Edizione | [3rd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2013 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 519.5/36 |
| Altri autori (Persone) |
LemeshowStanley
SturdivantRodney X |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Regression analysis
Anàlisi de regressió Anàlisi multivariable Estadística |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
1-118-54838-8
1-118-54835-3 1-299-40240-2 1-118-54839-6 |
| Classificazione | MAT029030 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Applied Logistic Regression; Contents; Preface to the Third Edition; 1 Introduction to the Logistic Regression Model; 1.1 Introduction; 1.2 Fitting the Logistic Regression Model; 1.3 Testing for the Significance of the Coefficients; 1.4 Confidence Interval Estimation; 1.5 Other Estimation Methods; 1.6 Data Sets Used in Examples and Exercises; 1.6.1 The ICU Study; 1.6.2 The Low Birth Weight Study; 1.6.3 The Global Longitudinal Study of Osteoporosis in Women; 1.6.4 The Adolescent Placement Study; 1.6.5 The Burn Injury Study; 1.6.6 The Myopia Study; 1.6.7 The NHANES Study
1.6.8 The Polypharmacy StudyExercises; 2 The Multiple Logistic Regression Model; 2.1 Introduction; 2.2 The Multiple Logistic Regression Model; 2.3 Fitting the Multiple Logistic Regression Model; 2.4 Testing for the Significance of the Model; 2.5 Confidence Interval Estimation; 2.6 Other Estimation Methods; Exercises; 3 Interpretation of the Fitted Logistic Regression Model; 3.1 Introduction; 3.2 Dichotomous Independent Variable; 3.3 Polychotomous Independent Variable; 3.4 Continuous Independent Variable; 3.5 Multivariable Models; 3.6 Presentation and Interpretation of the Fitted Values 3.7 A Comparison of Logistic Regression and Stratified Analysis for 2 x 2 TablesExercises; 4 Model-Building Strategies and Methods for Logistic Regression; 4.1 Introduction; 4.2 Purposeful Selection of Covariates; 4.2.1 Methods to Examine the Scale of a Continuous Covariate in the Logit; 4.2.2 Examples of Purposeful Selection; 4.3 Other Methods for Selecting Covariates; 4.3.1 Stepwise Selection of Covariates; 4.3.2 Best Subsets Logistic Regression; 4.3.3 Selecting Covariates and Checking their Scale Using Multivariable Fractional Polynomials; 4.4 Numerical Problems; Exercises 5 Assessing the Fit of the Model5.1 Introduction; 5.2 Summary Measures of Goodness of Fit; 5.2.1 Pearson Chi-Square Statistic, Deviance, and Sum-of-Squares; 5.2.2 The Hosmer-Lemeshow Tests; 5.2.3 Classification Tables; 5.2.4 Area Under the Receiver Operating Characteristic Curve; 5.2.5 Other Summary Measures; 5.3 Logistic Regression Diagnostics; 5.4 Assessment of Fit via External Validation; 5.5 Interpretation and Presentation of the Results from a Fitted Logistic Regression Model; Exercises; 6 Application of Logistic Regression with Different Sampling Models; 6.1 Introduction 6.2 Cohort Studies6.3 Case-Control Studies; 6.4 Fitting Logistic Regression Models to Data from Complex Sample Surveys; Exercises; 7 Logistic Regression for Matched Case-Control Studies; 7.1 Introduction; 7.2 Methods For Assessment of Fit in a 1-M Matched Study; 7.3 An Example Using the Logistic Regression Model in a 1-1 Matched Study; 7.4 An Example Using the Logistic Regression Model in a 1-M Matched Study; Exercises; 8 Logistic Regression Models for Multinomial and Ordinal Outcomes; 8.1 The Multinomial Logistic Regression Model 8.1.1 Introduction to the Model and Estimation of Model Parameters |
| Record Nr. | UNINA-9910139038403321 |
Hosmer David W
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| Hoboken, N.J., : Wiley, 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied Multivariate Statistical Analysis / / by Wolfgang Karl Härdle, Léopold Simar
| Applied Multivariate Statistical Analysis / / by Wolfgang Karl Härdle, Léopold Simar |
| Autore | Härdle Wolfgang |
| Edizione | [5th ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (xii, 558 pages) : 443 illustrations, 308 illustrations in color |
| Disciplina | 519.535 |
| Soggetto topico |
Statistics
Social sciences - Mathematics Econometrics Statistical Theory and Methods Statistics in Business, Management, Economics, Finance, Insurance Mathematics in Business, Economics and Finance Quantitative Economics Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Anàlisi multivariable Estadística econòmica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783030260064
3030260062 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Descriptive Techniques -- 1 Comparison of Batches -- Part II Multivariate Random Variables -- 2 A Short Excursion into Matrix Algebra -- 3 Moving to Higher Dimensions -- 4 Multivariate Distributions -- 5 Theory of the Multinormal -- 6 Theory of Estimation -- 7 Hypothesis Testing -- Part III Multivariate Techniques -- 8 Regression Models -- 9 Variable Selection.-10 Decomposition of Data Matrices by Factors -- 11 Principal Components Analysis -- 12 Factor Analysis -- 13 Cluster Analysis -- 14 Discriminant Analysis -- 15 Correspondence Analysis -- 16 Canonical Correlation Analysis -- 17 Multidimensional Scaling -- 18 Conjoint Measurement Analysis -- 19 Applications in Finance -- 20 Computationally Intensive Techniques -- Part IV Appendix -- A Symbols and Notations -- B Data -- Index -- References. |
| Record Nr. | UNINA-9910360852903321 |
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Härdle Wolfgang
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied Multivariate Statistics with R [[electronic resource] /] / by Daniel Zelterman
| Applied Multivariate Statistics with R [[electronic resource] /] / by Daniel Zelterman |
| Autore | Zelterman Daniel |
| Edizione | [2nd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (469 pages) |
| Disciplina | 570.285 |
| Collana | Statistics for Biology and Health |
| Soggetto topico |
Biometry
Bioinformatics Epidemiology Biostatistics Anàlisi multivariable Processament de dades R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031130052
9783031130045 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Elements of R -- Chapter 3. Graphical Displays -- Chapter 4. Basic Linear Algebra -- Chapter 5. The Univariate Normal Distribution -- Chapter 6. Bivariate Normal Distribution -- Chapter 7. Multivariate Normal Distribution -- Chapter 8. Factor Methods -- Chapter 9. Multivariate Linear Regression -- Chapter 10. Discrimination and Classification -- Chapter 11. Clustering Methods -- Chapter 12. Basic Models for Longitudinal Data -- Chapter 13. Time Series Models -- Chapter 14. Other Useful Methods. |
| Record Nr. | UNISA-996508571303316 |
|
Zelterman Daniel
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applied Multivariate Statistics with R / / by Daniel Zelterman
| Applied Multivariate Statistics with R / / by Daniel Zelterman |
| Autore | Zelterman Daniel |
| Edizione | [2nd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (469 pages) |
| Disciplina |
570.285
519.53502855133 |
| Collana | Statistics for Biology and Health |
| Soggetto topico |
Biometry
Bioinformatics Epidemiology Biostatistics Anàlisi multivariable Processament de dades R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031130052
9783031130045 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Elements of R -- Chapter 3. Graphical Displays -- Chapter 4. Basic Linear Algebra -- Chapter 5. The Univariate Normal Distribution -- Chapter 6. Bivariate Normal Distribution -- Chapter 7. Multivariate Normal Distribution -- Chapter 8. Factor Methods -- Chapter 9. Multivariate Linear Regression -- Chapter 10. Discrimination and Classification -- Chapter 11. Clustering Methods -- Chapter 12. Basic Models for Longitudinal Data -- Chapter 13. Time Series Models -- Chapter 14. Other Useful Methods. |
| Record Nr. | UNINA-9910645887003321 |
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Zelterman Daniel
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Classification and Data Science in the Digital Age / / edited by Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent
| Classification and Data Science in the Digital Age / / edited by Paula Brito, José G. Dias, Berthold Lausen, Angela Montanari, Rebecca Nugent |
| Autore | Brito Paula |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, : Springer Nature, 2023 |
| Descrizione fisica | 1 online resource (393 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
DiasJosé G
LausenBerthold MontanariAngela NugentRebecca |
| Collana | Studies in Classification, Data Analysis, and Knowledge Organization |
| Soggetto topico |
Artificial intelligence - Data processing
Machine learning Data mining Multivariate analysis Statistics - Computer programs Data Science Statistical Learning Machine Learning Data Mining and Knowledge Discovery Multivariate Analysis Statistical Software Intel·ligència artificial Aprenentatge automàtic Mineria de dades Anàlisi multivariable |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-09034-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- R. Abdesselam: A Topological Clustering of Individuals -- C. Anton and I. Smith: Model Based Clustering of Functional Data with Mild Outliers -- F. Antonazzo and S. Ingrassia: A Trivariate Geometric Classification of Decision Boundaries for Mixtures of Regressions -- E. Arnone, E. Cunial, and L. M. Sangalli: Generalized Spatio-temporal Regression with PDE Penalization -- R. Ascari and S. Migliorati: A New Regression Model for the Analysis of Microbiome Data -- R. Aschenbruck, G. Szepannek, and A. F. X. Wilhelm: Stability of Mixed-type Cluster Partitions for Determination of the Number of Clusters -- A. Ashofteh and P. Campos: A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment -- V. Batagelj: Clustering and Blockmodeling Temporal Networks – Two Indirect Approaches -- R. Boutalbi, L. Labiod, and M. Nadif: Latent Block Regression Model -- N. Chabane, M. Achraf Bouaoune, R. Amir Sofiane Tighilt, B. Mazoure, N. Tahiri, and V. Makarenkov: Using Clustering and Machine Learning Methods to Provide Intelligent Grocery Shopping Recommendations -- T. Chadjipadelis and S. Magopoulou: COVID-19 Pandemic: a Methodological Model for the Analysis of Government’s Preventing Measures and Health Data Records -- J. Champagne Gareau, É. Beaudry, and V. Makarenkov: pcTVI: Parallel MDP Solver Using a Decomposition into Independent Chains -- C. Di Nuzzo and S. Ingrassia: Three-way Spectral Clustering -- J. Dobša and H. A. L. Kiers: Improving Classification of Documents by Semi-supervised Clustering in a Semantic Space -- J. Gama: Trends in Data Stream Mining -- L. A. García-Escudero, A. Mayo-Iscar, G. Morelli, and M. Riani: Old and New Constraints in Model Based Clustering -- V. G Genova, G. Giordano, G . Ragozini, and M. Prosperina Vitale: Clustering Student Mobility Data in 3-way Networks -- R. Giubilei: Clustering Brain Connectomes Through a Density-peak Approach -- T. Górecki, M. Šuczak, and P. Piasecki: Similarity Forest for Time Series Classification -- K. Hayashi, E. Hoshino, M. Suzuki, E. Nakanishi, K. Sakai, and M. Obatake: Detection of the Biliary Atresia Using Deep Convolutional Neural Networks Based on Statistical Learning Weights via Optimal Similarity and Resampling Methods -- Ch. Hennig: Some Issues in Robust Clustering -- J. Kalina and P. Janá£ek: Robustness Aspects of Optimized Centroids -- L. Labiod and M. Nadif: Data Clustering and Representation Learning Based on Networked Data -- Lazhar Labiod and Mohamed Nadif: Towards a Bi-stochastic Matrix Approximation of k-means and Some Variants -- A. LaLonde, T. Love, D. R. Young, and T. Wu: Clustering Adolescent Female Physical Activity Levels with an Infinite Mixture Model on Random Effects -- Á. López-Oriona, J. A. Vilar, and P. D’Urso: Unsupervised Classification of Categorical Time Series Through Innovative Distances -- D. Masís, E. Segura, J. Trejos, and A. Xavier: Fuzzy Clustering by Hyperbolic Smoothing -- R. Meng, H. K. H. Lee, and K. Bouchard: Stochastic Collapsed Variational Inference for Structured Gaussian Process Regression Networks -- H. Duy Nguyen, F. Forbes, G. Fort, and O. Cappé: An Online Minorization-Maximization Algorithm -- L. Palazzo and R. Ievoli: Detecting Differences in Italian Regional Health Services During Two Covid-19 Waves -- G. Panagiotidou and T. Chadjipadelis: Political and Religion Attitudes in Greece: Behavioral Discourses -- K. Pawlasová, I. Karafiátová, and J. Dvořák: Supervised Classification via Neural Networks for Replicated Point Patterns -- G. Perrone and G. Soffritti: Parsimonious Mixtures of Seemingly Unrelated Contaminated Normal Regression Models -- N. Pronello, R. Ignaccolo, L. Ippoliti, and S. Fontanella: Penalized Model-based Functional Clustering: a Regularization Approach via Shrinkage Methods -- D. Rodrigues, L. P. Reis, and B. M. Faria: Emotion Classification Based on Single Electrode Brain Data: Applications for Assistive Technology -- R. Scimone, A. Menafoglio, L. M. Sangalli, and P. Secchi: The Death Process in Italy Before and During the Covid-19 Pandemic: a Functional Compositional Approach -- O. Silva, Á. Sousa, and H. Bacelar-Nicolau: Clustering Validation in the Context of Hierarchical Cluster Analysis: an Empirical Study -- C. Silvestre, M. G. M. S. Cardoso, and M. Figueiredo: An MML Embedded Approach for Estimating the Number of Clusters -- Á. Sousa, O. Silva, M. Graça Batista, S. Cabral, and H. Bacelar-Nicolau: Typology of Motivation Factors for Employees in the Banking Sector: An Empirical Study Using Multivariate Data Analysis Methods -- J. Michael Spoor, J. Weber, and J. Ovtcharova: A Proposal for Formalization and Definition of Anomalies in Dynamical Systems -- N. Tahiri and A. Koshkarov: New Metrics for Classifying Phylogenetic Trees Using -means and the Symmetric Difference Metric -- S. D. Tomarchio: On Parsimonious Modelling via Matrix-variate t Mixtures -- G. Zammarchi, M. Romano, and C. Conversano: Evolution of Media Coverage on Climate Change and Environmental Awareness: an Analysis of Tweets from UK and US Newspapers. |
| Record Nr. | UNINA-9910768481303321 |
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Brito Paula
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| Cham, : Springer Nature, 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Compositional data analysis : theory and applications / / edited by Vera Pawlowsky-Glahn, Antonella Buccianti
| Compositional data analysis : theory and applications / / edited by Vera Pawlowsky-Glahn, Antonella Buccianti |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2011 |
| Descrizione fisica | 1 online resource (402 p.) |
| Disciplina | 519.5/35 |
| Altri autori (Persone) |
Pawlowsky-GlahnVera
BucciantiAntonella |
| Soggetto topico |
Multivariate analysis
Correlation (Statistics) Anàlisi multivariable Correlació (Estadística) |
| ISBN |
9786613204516
9781283204514 1283204517 9781119976462 1119976464 9781119976479 1119976472 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Introduction -- pt. 2. Theory-- statistical modelling -- pt. 3. Theory-- algebra and calculus -- pt. 4. Applications -- pt. 5. Software. |
| Record Nr. | UNINA-9910133221303321 |
| Hoboken, N.J., : Wiley, 2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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High-dimensional covariance matrix estimation : an introduction to random matrix theory / / Aygul Zagidullina
| High-dimensional covariance matrix estimation : an introduction to random matrix theory / / Aygul Zagidullina |
| Autore | Zagidullina Aygul |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (123 pages) |
| Disciplina | 512.9434 |
| Collana | SpringerBriefs in Applied Statistics and Econometrics |
| Soggetto topico |
Random matrices
Asymptotic efficiencies (Statistics) Multivariate analysis Matrius aleatòries Anàlisi multivariable |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-80065-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466409803316 |
|
Zagidullina Aygul
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Innovations in Multivariate Statistical Modeling [[electronic resource] ] : Navigating Theoretical and Multidisciplinary Domains / / edited by Andriëtte Bekker, Johannes T. Ferreira, Mohammad Arashi, Ding-Geng Chen
| Innovations in Multivariate Statistical Modeling [[electronic resource] ] : Navigating Theoretical and Multidisciplinary Domains / / edited by Andriëtte Bekker, Johannes T. Ferreira, Mohammad Arashi, Ding-Geng Chen |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (434 pages) |
| Disciplina | 780 |
| Collana | Emerging Topics in Statistics and Biostatistics |
| Soggetto topico |
Statistics
Applied Statistics Statistical Theory and Methods Anàlisi multivariable |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-13971-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- PART 1: Trends in Multi- and Matrix-Variate Analysis -- Q. Guo, X. Deng and N. Ravishanker: Association-based Optimal Subpopulation Selection of Multivariate Data -- T. B. Mattos, L. A. Matos, V. H Lachos Aldo: Likelihood-Based Inference For Linear Mixed-Effects Models With Censored Response Using Skew-Normal Distribution -- Y. Melnykov, M. Perry, V. Melnykov: Robust Estimation of Multiple Change Points in Multivariate Processes -- T. Botha, J. T Ferreira and A. Bekker: Some Computational Aspects Of A Noncentral Dirichlet Family -- Y. Murat Bulut and Olcay Arslan: Modeling Handwritten Digits Dataset Using The Matrix Variate T Distribution -- B. Byukusenge, D. von Rosen and M. Singull: On The Identification Of Extreme Elements In A Residual For The Gmanova-Manova Model -- M. Billio, R. Casarin, M. Costola and M. Iacopini: Matrix-variate Smooth Transition Models for Temporal Networks -- H. Baghishani and J. Ownuk: A Flexible Matrix-Valued Response Regression For Skewed Data -- J. Trink, H. Haghbin and M. Maadooliat: Multivariate Functional Singular Spectrum Analysis: A Nonparametric Approach for Analyzing Functional Time Series -- M. Greenacre: Compositional Data Analysis — Linear Algebra, Visualization And Interpretation -- A. Alzaatreh, F. Famoye and C. Lee: Multivariate Count Data Regression Models And Their Applications -- A. Iranmanesh, M. Rafiei and D. Nagar: A Generalized Multivariate Gamma Distribution -- PART 2: Aspects of High Dimensional Methodology and Bayesian Learning -- G. D' Angella and C. Hennig: A Comparison Of Different Clustering Approaches For High-Dimensional Presence-Absence Data -- S. Millard, M. Arashi and G. Maribe: High-Dimensional Feature Selection For Logistic Regression Using Blended Penalty Functions -- I. Munaweera, S. Muthukumarana and M. Jafari Jozani: A Generalized Quadratic Garrote Approach Towards Ridge Regression Analysis -- M. Roozbeh: High Dimensional Nonlinear Optimization Problem In Semiparametric Regression Model -- PART 3: Frontiers in Robust Analysis and Mixture Modelling -- A. Punzo and S. D. Tomarchia: Parsimonious Finite Mixtures Of Matrix-Variate Regressions -- F. Zehra Doğru and Olcay Arslan:Robust Multivariate Modelling for Heterogeneous Data Sets With Mixtures of Multivariate Skew Laplace Normal Distributions -- M. Norouzirad, M. Arashi, F. J Marques and F. Esmaeili: Robust Estimation Through Preliminary Testing Based On The Lad-Lasso. |
| Record Nr. | UNISA-996503550403316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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