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Bayesian Statistics and New Generations [[electronic resource] ] : BAYSM 2018, Warwick, UK, July 2-3 Selected Contributions / / edited by Raffaele Argiento, Daniele Durante, Sara Wade
| Bayesian Statistics and New Generations [[electronic resource] ] : BAYSM 2018, Warwick, UK, July 2-3 Selected Contributions / / edited by Raffaele Argiento, Daniele Durante, Sara Wade |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XI, 184 p. 40 illus., 29 illus. in color.) |
| Disciplina | 519.5 |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Statistics
Computer simulation Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Business, Management, Economics, Finance, Insurance Statistics for Life Sciences, Medicine, Health Sciences Simulation and Modeling |
| ISBN | 3-030-30611-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I – Theory and Methods: A. Diana, J. Griffin, and E. Matechou, A Polya Tree Based Model for Unmarked Individuals in an Open Wildlife Population -- S. Haque and K. Mengersen, Bias Estimation and Correction Using Bootstrap Simulation of the Linking Process -- N. Laitonjam and N. Hurley, Non-parametric Overlapping Community Detection -- L. Fee Schneider, T. Staudt, and A. Munk, Posterior Consistency in the Binomial Model with Unknown Parameters: A Numerical Study -- C. Spire and D. Chakrabarty, Learning in the Absence of Training Data - a Galactic Application -- D. Tait and B. Worton, Multiplicative Latent Force Models -- PART II – Computational Statistics: N. Cunningham, J. E. Griffin, D. L. Wild, and A. Lee, particleMDI: A Julia Package for the Integrative Cluster Analysis of Multiple Datasets -- D. Hosszejni and G. Kastner, Approaches Toward the Bayesian Estimation of the Stochastic Volatility Model with Leverage -- B. Karimi and M. Lavielle, Efficient Metropolis-Hastings Sampling for Nonlinear Mixed Effects Models -- G. Kratzer, Reinhard Furrer, and Pittavino Marta. Comparison Between Suitable Priors for Additive Bayesian Networks -- I. Peneva and R. Savage, A Bayesian Nonparametric Model for Integrative Clustering of Omics Data -- I. Schwabe, Bayesian Inference of Interaction Effects in Item-Level Hierarchical Twin Data -- PART III – Applied Statistics: K. Brock, L. Billingham, C. Yap, and G. Middleton, A Phase II Clinical Trial Design for Associated Co-Primary Efficacy and Toxicity Outcomes with Baseline Covariates -- E. Lanzarone, E. Scalco, A. Mastropietro, S. Marzi, and G. Rizzo, A Conditional Autoregressive Model for estimating Slow and Fast Diffusion from Magnetic Resonance Images -- D. Rocha, M. Scotto, C. Pinto, J. Nuno Tavares, and S. Gouveia, Simulation Study of HIV Temporal Patterns Using Bayesian Methodology -- A. Shenvi, J. Smith, R. Walton, and S. Eldridge, Modelling with Non-Stratified Chain Event Graphs -- O. Stevenson and B. Brewer, Modelling Career Trajectories of Cricket Players Using Gaussian Processes -- F. Turner, R. Wilkinson, C. Buck, J. Jones, and L. Sime, Ice Cores and Emulation: Learning More About Past Ice Sheet Shapes. |
| Record Nr. | UNINA-9910360852703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Statistics from Methods to Models and Applications [[electronic resource] ] : Research from BAYSM 2014 / / edited by Sylvia Frühwirth-Schnatter, Angela Bitto, Gregor Kastner, Alexandra Posekany
| Bayesian Statistics from Methods to Models and Applications [[electronic resource] ] : Research from BAYSM 2014 / / edited by Sylvia Frühwirth-Schnatter, Angela Bitto, Gregor Kastner, Alexandra Posekany |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (175 p.) |
| Disciplina | 519.542 |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics for Business, Management, Economics, Finance, Insurance Statistics and Computing/Statistics Programs |
| ISBN | 3-319-16238-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | On Bayesian based adaptive confidence sets for linear functionals -- A new finite approximation for the NGG mixture model: an application to density estimation -- Distributed Estimation of Mixture Models -- Bayesian Survival Model based on Moment Characterization -- Identifying the Infectious Period Distribution for Stochastic Epidemic Models Using the Posterior Predictive Check -- A subordinated stochastic process model -- Jeffreys priors for mixture estimation -- Bayesian Variable Selection for Generalized Linear Models Using the Power-Conditional-Expected-Posterior Prior -- A new strategy for testing cosmology with simulations -- Mixture Model for Filtering Firms' Profit Rates -- Bayesian Estimation of the Aortic Stiffness based on Non-Invasive Computed Tomography Images -- Formal and Heuristic Model Averaging Methods for Predicting the US Unemployment Rate -- Bayesian Filtering for Thermal Conductivity Estimation given Temperature Observations -- Application of Interweaving in DLMs to an Exchange and Specialization Experiment. |
| Record Nr. | UNINA-9910299782403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian statistics in action [[electronic resource] ] : BAYSM 2016, Florence, Italy, June 19-21 / / edited by Raffaele Argiento, Ettore Lanzarone, Isadora Antoniano Villalobos, Alessandra Mattei
| Bayesian statistics in action [[electronic resource] ] : BAYSM 2016, Florence, Italy, June 19-21 / / edited by Raffaele Argiento, Ettore Lanzarone, Isadora Antoniano Villalobos, Alessandra Mattei |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (IX, 251 p. 56 illus., 44 illus. in color.) |
| Disciplina | 519.542 |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Social Sciences, Humanities, Law Statistics for Business, Management, Economics, Finance, Insurance |
| ISBN | 3-319-54084-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I THEORY AND METHODS -- 1 Sequential Monte Carlo methods in random intercept models for longitudinal data -- 2 On the truncation error of a superposed gamma process -- 3 On the study of two models for integer valued high-frequency data -- 4 Identification and Estimation of Principal Causal Effects in Randomized Experiments with Treatment Switching -- 5 A Bayesian Joint Dispersion Model with Flexible Links -- 6 Local posterior concentration rate for multilevel sparse sequences -- 7 Likelihood Tempering in Dynamic Model Averaging -- 8 Localization in High-Dimensional Monte Carlo Filtering -- 9 Linear inverse problem with range prior on correlations and its Variational Bayes. Part II APPLICATIONS AND CASE STUDIES -- 10 Bayesian hierarchical model for assessment of climate model biases -- 11 An application of Bayesian seemingly unrelated regression models with flexible tails -- 12 Bayesian Inference of Stochastic Pursuit Models from Basketball Tracking Data -- 13 Identification of patient-specific parameters in a kinetic model of fluid and mass transfer during dialysis -- 14 A Bayesian nonparametric approach to ecological risk assessment -- 15 Approximate Bayesian Computation Methods in the identification of atmospheric contamination sources for DAPPLE experiment -- 16 Bayesian survival analysis to model plant resistance and tolerance to virus diseases -- 17 Randomization Inference and Bayesian Inference in Regression Discontinuity Design: An application to Italian University grants -- 18 Bayesian methods for microsimulation models -- 19 A Bayesian Model for Describing and Predicting the Stochastic Demand of Emergency Calls -- 20 Flexible Parallel Split-Merge MCMC for the HDP -- 21 Bayesian Inference for Continuous Time Animal Movement Based on Steps and Turns -- 22 Explaining the Lethality of Boko Haram’s Terrorist Attacks in Nigeria, 2009-2014: A Hierarchical Bayesian Approach -- 23 Optimizing movement of cooperating pedestrians by exploiting floor-field model and Markov decision process. |
| Record Nr. | UNINA-9910254298103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Beginning data science with R [[electronic resource] /] / by Manas A. Pathak
| Beginning data science with R [[electronic resource] /] / by Manas A. Pathak |
| Autore | Pathak Manas A |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (165 p.) |
| Disciplina |
519
519.5 620 621.382 |
| Soggetto topico |
Applied mathematics
Engineering mathematics Statistics Signal processing Image processing Speech processing systems R (Computer program language) Mathematical and Computational Engineering Statistics and Computing/Statistics Programs Signal, Image and Speech Processing |
| ISBN | 3-319-12066-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Overview of the R Programming Language -- Getting Data into R -- Data Visualization -- Exploratory Data Analysis -- Regression -- Classification -- Text Mining. . |
| Record Nr. | UNINA-9910299994103321 |
Pathak Manas A
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Beginning SQL Server R Services [[electronic resource] ] : Analytics for Data Scientists / / by Bradley Beard
| Beginning SQL Server R Services [[electronic resource] ] : Analytics for Data Scientists / / by Bradley Beard |
| Autore | Beard Bradley |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2016 |
| Descrizione fisica | 1 online resource (XX, 261 p. 284 illus., 275 illus. in color.) |
| Disciplina | 005.74 |
| Soggetto topico |
Database management
Statistics Data mining Programming languages (Electronic computers) R (Computer program language) SQL (Computer program language) Database Management Statistics and Computing/Statistics Programs Data Mining and Knowledge Discovery Programming Languages, Compilers, Interpreters |
| ISBN | 1-4842-2298-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910150189703321 |
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Beard Bradley
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| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big and Complex Data Analysis [[electronic resource] ] : Methodologies and Applications / / edited by S. Ejaz Ahmed
| Big and Complex Data Analysis [[electronic resource] ] : Methodologies and Applications / / edited by S. Ejaz Ahmed |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XIV, 386 p. 85 illus., 55 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Contributions to Statistics |
| Soggetto topico |
Statistics
Big data Biostatistics Data mining Statistical Theory and Methods Statistics and Computing/Statistics Programs Big Data/Analytics Data Mining and Knowledge Discovery |
| ISBN | 3-319-41573-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Introduction -- Unsupervised Bump Hunting Using Principal Components -- Statistical Process Control Charts as a Tool for Analyzing Big Data -- Empirical Likelihood Test for High Dimensional Generalized Linear Models -- Identifying gene-environment interactions associated with prognosis using penalized quantile regression -- A Computationally Efficient Approach for Modeling Complex and Big Survival Data -- Regularization after marginal learning for ultra-high dimensional regression models -- Tests of concentration for low-dimensional and high-dimensional directional data -- Random Projections For Large-Scale Regression -- How Different are Estimated Genetic Networks of Cancer Subtypes? -- Analysis of correlated data with error-prone response under generalized linear mixed models -- High-Dimensional Classification for Brain Decoding -- Optimal shrinkage estimation in heteroscedastic hierarchical linear models -- Bias-reduced moment estimators of Population Spectral Distribution and their applications -- Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values -- A Mixture of Variance-Gamma Factor Analyzers -- Fast Community Detection in Complex Networks with a K-Depths Classifier. |
| Record Nr. | UNINA-9910254293703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data Analytics [[electronic resource] ] : Methods and Applications / / edited by Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao
| Big Data Analytics [[electronic resource] ] : Methods and Applications / / edited by Saumyadipta Pyne, B.L.S. Prakasa Rao, S.B. Rao |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | New Delhi : , : Springer India : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (276 pages) |
| Disciplina | 519.5 |
| Soggetto topico |
Statistics
Data mining Applied mathematics Engineering mathematics Statistics and Computing/Statistics Programs Statistics for Life Sciences, Medicine, Health Sciences Statistics for Social Sciences, Humanities, Law Statistics for Business, Management, Economics, Finance, Insurance Data Mining and Knowledge Discovery Applications of Mathematics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction: The Promises and Challenges of Big Data Analytics -- Chapter 2. Massive Data Analysis: Tasks, Tools, Applications and Challenges -- Chapter 3. Statistical Challenges with Big Data in Management Science -- Chapter 4. Application of Mixture Models to Large Datasets -- Chapter 5. An Efficient Partition-Repetition Approach in Clustering of Big Data -- Chapter 6. Multithreaded Graph Algorithms for Large-scale Analytics -- Chapter 7. On-line Graph Partitioning with an Affine Message Combining Cost Function -- Chapter 8. Big Data Analytics Platforms for Real-time Applications in IoT -- Chapter 9. Complex Event Processing in Big Data Systems -- Chapter 10. Unwanted Traffic Identification in Large-scale University Networks: A Case Study -- Chapter 11. Application-Level Benchmarking of Big Data Systems -- Chapter 12. Managing Large Scale Standardized Electronic Healthcare Records -- Chapter 13. Microbiome Data Mining for Microbial Interactions and Relationships -- Chapter 14. A Nonlinear Technique for Analysis of Big Data in Neuroscience -- Chapter 15. Big Data and Cancer Research. |
| Record Nr. | UNINA-9910136605803321 |
| New Delhi : , : Springer India : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Business Statistics for Competitive Advantage with Excel 2013 [[electronic resource] ] : Basics, Model Building, Simulation and Cases / / by Cynthia Fraser
| Business Statistics for Competitive Advantage with Excel 2013 [[electronic resource] ] : Basics, Model Building, Simulation and Cases / / by Cynthia Fraser |
| Autore | Fraser Cynthia |
| Edizione | [3rd ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XIV, 449 p. 406 illus. in color.) |
| Disciplina | 005.54 |
| Soggetto topico |
Statistics
Business Management science Statistics for Business, Management, Economics, Finance, Insurance Statistics and Computing/Statistics Programs Statistics, general Business and Management, general |
| ISBN | 1-4614-7381-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistics for Decision Making and Competitive Advantage -- Describing Your Data Chapter -- Hypothesis Tests, Confidence Intervals, and Simulation to Infer Population Characteristics and Differences -- Quantifying the Influence of Performance Drivers and Forecasting: Regression -- Market Simulation and Segmentation with Descriptive Statistics, Inference, Hypothesis Tests, and Regression -- Finance Application: Portfolio Analysis with a Market Index as a Leading Indicator in Simple Linear Regression -- Association between Two Categorical Variables: Contingency Analysis with Chi Square -- Building Multiple Regression Models -- Model Building and Forecasting with Multicollinear Time Series -- Indicator Variables -- Nonlinear Multiple Regression Models -- Indicator Interactions for Segment Differences or Changes in Response -- Logit Regression for Bounded Responses -- Index. |
| Record Nr. | UNINA-9910438136303321 |
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Fraser Cynthia
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| New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Campionamento da popolazioni finite [[electronic resource] ] : Il disegno campionario / / by Pier Luigi Conti, Daniela Marella
| Campionamento da popolazioni finite [[electronic resource] ] : Il disegno campionario / / by Pier Luigi Conti, Daniela Marella |
| Autore | Conti Pier Luigi |
| Edizione | [1st ed. 2012.] |
| Pubbl/distr/stampa | Milano : , : Springer Milan : , : Imprint : Springer, , 2012 |
| Descrizione fisica | 1 online resource (450 p.) |
| Disciplina | 519.5 |
| Collana | Collana di Statistica e Probabilità Applicata |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics for Social Sciences, Humanities, Law Statistics and Computing/Statistics Programs |
| ISBN | 88-470-2577-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Nota di contenuto |
Title Page; Copyright Page; Prefazione; Table of Contents; 1 Aspetti generali sul campionamento dapopolazioni finite; 1.1 Rilevazioni censuarie e rilevazioni campionarie; 1.2 Linee metodologiche di una rilevazione statistica; 1.3 Popolazioni, etichette, modalit`a etichettate; 1.4 Popolazioni suddivise in sottopopolazioni; 1.5 Liste di unit`a di campionamento; 1.6 Rilevazioni statistiche e indagini statistiche; 1.7 Fonti di errore e distorsioni; 1.8 Come non progettare una rilevazione campionaria; 1.9 Campionamento non probabilistico; 2 Campionamento probabilistico
2.1 Disegni campionari: definizione e propriet`a di base2.2 Implementazione di disegni campionari medianteschemi: brevi cenni; 2.3 Dati campionari etichettati; 2.4 Inferenza da popolazioni finite e inferenza damodello: due approcci a confronto; 2.5 Stimatori e loro propriet`; 2.6 Intervalli di confidenza; Esercizi; 3 Disegno campionario semplice; 3.1 Il disegno semplice senza ripetizione; 3.1.1 Definizione del disegno semplice senza ripetizione; 3.1.2 Simmetria totale del disegno semplice senzaripetizione; 3.1.3 Implementazione del disegno semplice senzaripetizione 4.2 Scelta della numerosit`a campionaria per la stima diproporzioni4.3 Scelta della numerosit`a campionaria per la stima dimedie; 4.4 Scelta della numerosit`a campionaria con approcciodecisionale*; Esercizi; 5 Stima con il metodo della regressione; 5.1 L'uso di caratteri ausiliari: aspetti di base; 5.2 Lo stimatore alle differenze; 5.3 Lo stimatore per regressione; 5.4 Distorsione e varianza approssimate dello stimatoreper regressione; 5.5 Stima della varianza dello stimatore per regressione; Esercizi; 6 Stima con il metodo del quoziente 7.4.3 Considerazioni sul caso in cui le varianze deglistrati siano incognite |
| Record Nr. | UNINA-9910484490603321 |
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Conti Pier Luigi
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| Milano : , : Springer Milan : , : Imprint : Springer, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Characterizing Interdependencies of Multiple Time Series [[electronic resource] ] : Theory and Applications / / by Yuzo Hosoya, Kosuke Oya, Taro Takimoto, Ryo Kinoshita
| Characterizing Interdependencies of Multiple Time Series [[electronic resource] ] : Theory and Applications / / by Yuzo Hosoya, Kosuke Oya, Taro Takimoto, Ryo Kinoshita |
| Autore | Hosoya Yuzo |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (X, 133 p. 32 illus.) |
| Disciplina | 519.55 |
| Collana | JSS Research Series in Statistics |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics for Life Sciences, Medicine, Health Sciences Statistics for Business, Management, Economics, Finance, Insurance Statistics for Social Sciences, Humanities, Law Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
| ISBN | 981-10-6436-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1: Introduction to statistical causal analysis -- 2: Measures of one-way effect, reciprocity and association -- 3: Partial measures of interdependence -- 4: Inference based on the vector autoregressive and moving average model -- 5: Inference on change in causality measures -- 6: Simulation performance of estimation methods -- 7: Empirical analysis of macroeconomic series -- 8: Empirical analysis of change in causality measures -- 9: Conclusion -- Appendix -- References -- Index. |
| Record Nr. | UNINA-9910254287703321 |
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Hosoya Yuzo
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| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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