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Applied Time Series Analysis and Forecasting with Python [[electronic resource] /] / by Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python [[electronic resource] /] / by Changquan Huang, Alla Petukhina |
| Autore | Huang Changquan |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (377 pages) |
| Disciplina | 813 |
| Collana | Statistics and Computing |
| Soggetto topico |
Time-series analysis
Statistics - Computer programs Econometrics Python (Computer program language) Machine learning Statistics Time Series Analysis Statistical Software Python Machine Learning Statistics in Business, Management, Economics, Finance, Insurance Anàlisi de sèries temporals Python (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-13584-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Time Series Concepts and Python -- 2. Exploratory Time Series Data Analysis -- 3. Stationary Time Series Models -- 4. ARMA and ARIMA Modeling and Forecasting -- 5. Nonstationary Time Series Models -- 6. Financial Time Series and Related Models -- 7. Multivariate Time Series Analysis -- 8. State Space Models and Markov Switching Models -- 9. Nonstationarity and Cointegrations -- 10. Modern Machine Learning Methods for Time Series Analysis. |
| Record Nr. | UNISA-996495169403316 |
Huang Changquan
|
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Applied Time Series Analysis and Forecasting with Python / / by Changquan Huang, Alla Petukhina
| Applied Time Series Analysis and Forecasting with Python / / by Changquan Huang, Alla Petukhina |
| Autore | Huang Changquan |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (377 pages) |
| Disciplina |
813
519.55 |
| Collana | Statistics and Computing |
| Soggetto topico |
Time-series analysis
Statistics - Computer programs Econometrics Python (Computer program language) Machine learning Statistics Time Series Analysis Statistical Software Python Machine Learning Statistics in Business, Management, Economics, Finance, Insurance Anàlisi de sèries temporals Python (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-13584-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Time Series Concepts and Python -- 2. Exploratory Time Series Data Analysis -- 3. Stationary Time Series Models -- 4. ARMA and ARIMA Modeling and Forecasting -- 5. Nonstationary Time Series Models -- 6. Financial Time Series and Related Models -- 7. Multivariate Time Series Analysis -- 8. State Space Models and Markov Switching Models -- 9. Nonstationarity and Cointegrations -- 10. Modern Machine Learning Methods for Time Series Analysis. |
| Record Nr. | UNINA-9910619280803321 |
|
Huang Changquan
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 International Publishing : , : Imprint : Springer, , 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 International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational Finance with R [[electronic resource] /] / by Rituparna Sen, Sourish Das
| Computational Finance with R [[electronic resource] /] / by Rituparna Sen, Sourish Das |
| Autore | Sen Rituparna |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (352 pages) |
| Disciplina | 332.028553 |
| Collana | Indian Statistical Institute Series |
| Soggetto topico |
Statistics
Social sciences - Mathematics Stochastic analysis Machine learning Statistics - Computer programs Statistics in Business, Management, Economics, Finance, Insurance Mathematics in Business, Economics and Finance Stochastic Analysis Machine Learning Statistical Software Enginyeria financera R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-19-2008-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I. Numerical Methods -- 1. Preliminaries -- 2. Solving a System of Linear Equations -- 3. Solving Non-Linear Equations -- 4. Numerical Integration -- 5. Numerical Differentiation -- 6. Numerical Methods for PDE -- 7. Optimization -- Part II. Simulation Methods -- 8. Monte-Carlo Methods -- 9. Lattice Models -- 10. Simulating Brownian Motion -- 11. Variance Reduction -- 12. Bayesian Computation with Stan -- 13. Resampling -- Part III. Statistical Methods -- 14. Descriptive Methods -- 15. Inferential Statistics -- 16. Statistical Risk Analysis -- 17. Multivariate Analysis -- 18. Univariate Time Series -- 19. Multivariate Time Series -- 20. High Frequency Data -- 21. Supervised Learning -- 22. Unsupervised Learning -- Appendix -- A. Basics of Mathematical Finance -- B. Introduction to R -- C. Extreme Value Theory in Finance -- Bibliography. . |
| Record Nr. | UNINA-9910733712103321 |
|
Sen Rituparna
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Empirical inference : festschrift in honor of Vladimir N. Vapnik / / Bernhard Scholkopf, Zhiyuan Luo, Vladimir Vovk, editors
| Empirical inference : festschrift in honor of Vladimir N. Vapnik / / Bernhard Scholkopf, Zhiyuan Luo, Vladimir Vovk, editors |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Heidelberg, Germany : , : Springer, , 2013 |
| Descrizione fisica | 1 online resource (xix, 287 pages) : illustrations (some color) |
| Disciplina | 006.31 |
| Collana | Gale eBooks |
| Soggetto topico |
Probabilities
Statistics - Computer programs |
| ISBN | 3-642-41136-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I - History of Statistical Learning Theory -- Chap. 1 - In Hindsight: Doklady Akademii Nauk SSSR, 181(4), 1968 -- Chap. 2 - On the Uniform Convergence of the Frequencies of Occurrence of Events to Their Probabilities -- Chap. 3 - Early History of Support Vector Machines -- Part II - Theory and Practice of Statistical Learning Theory -- Chap. 4 - Some Remarks on the Statistical Analysis of SVMs and Related Methods -- Chap. 5 - Explaining AdaBoost -- Chap. 6 - On the Relations and Differences Between Popper Dimension, Exclusion Dimension and VC-Dimension -- Chap. 7 - On Learnability, Complexity and Stability -- Chap. 8 - Loss Functions -- Chap. 9 - Statistical Learning Theory in Practice -- Chap. 10 - PAC-Bayesian Theory -- Chap. 11 - Kernel Ridge Regression -- Chap. 12 - Multi-task Learning for Computational Biology: Overview and Outlook -- Chap. 13 - Semi-supervised Learning in Causal and Anticausal Settings -- Chap. 14 - Strong Universal Consistent Estimate of the Minimum Mean-Squared Error -- Chap. 15 - The Median Hypothesis -- Chap. 16 - Efficient Transductive Online Learning via Randomized Rounding -- Chap. 17 - Pivotal Estimation in High-Dimensional Regression via Linear Programming -- Chap. 18 - Some Observations on Sparsity Inducing Regularization Methods for Machine Learning -- Chap. 19 - Sharp Oracle Inequalities in Low Rank Estimation -- Chap. 20 - On the Consistency of the Bootstrap Approach for Support Vector Machines and Related Kernel-Based Methods -- Chap. 21 - Kernels, Pre-images and Optimization -- Chap. 22 - Efficient Learning of Sparse Ranking Functions -- Chap. 23 - Direct Approximation of Divergences Between Probability Distributions -- Index. |
| Record Nr. | UNINA-9910437566303321 |
| Heidelberg, Germany : , : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910453567003321 |
|
Nelson Stephen L.
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||
| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910790926503321 |
|
Nelson Stephen L.
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson
| Excel data analysis for dummies / / by Stephen L. Nelson and E. C. Nelson |
| Autore | Nelson Stephen L. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , 2014 |
| Descrizione fisica | 1 online resource (363 p.) |
| Disciplina | 005.54 |
| Collana | For Dummies |
| Soggetto topico |
Statistics - Data processing
Statistics - Computer programs |
| ISBN | 1-118-89810-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Title Page; Copyright Page; Contents at a Glance; Table of Contents; Introduction; About This Book; What You Can Safely Ignore; What You Shouldn't Ignore (Unless You're a Masochist); Foolish Assumptions; How This Book Is Organized; Icons Used in This Book; Beyond the Book; Where to Go from Here; Part I: Where's the Beef?; Chapter 1: Introducing Excel Tables; What Is a Table and Why Do I Care?; Building Tables; Analyzing Table Information; Chapter 2: Grabbing Data from External Sources; Getting Data the Export-Import Way; Querying External Databases and Web Page Tables
It's Sometimes a Raw DealChapter 3: Scrub-a-Dub-Dub: Cleaning Data; Editing Your Imported Workbook; Cleaning Data with Text Functions; Using Validation to Keep Data Clean; Part II: PivotTables and PivotCharts; Chapter 4: Working with PivotTables; Looking at Data from Many Angles; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Table; Customizing How Pivot Tables Work and Look; Chapter 5: Building PivotTable Formulas; Adding Another Standard Calculation; Creating Custom Calculations; Using Calculated Fields and Items; Retrieving Data from a Pivot Table Chapter 6: Working with PivotChartsWhy Use a Pivot Chart?; Getting Ready to Pivot; Running the PivotTable Wizard; Fooling Around with Your Pivot Chart; Using Chart Commands to Create Pivot Charts; Chapter 7: Customizing PivotCharts; Selecting a Chart Type; Working with Chart Styles; Changing Chart Layout; Changing a Chart's Location; Formatting the Plot Area; Formatting the Chart Area; Formatting 3-D Charts; Part III: Advanced Tools; Chapter 8: Using the Database Functions; Quickly Reviewing Functions; Using the DAVERAGE Function; Using the DCOUNT and DCOUNTA Functions Using the DGET FunctionUsing the DMAX and DMAX Functions; Using the DPRODUCT Function; Using the DSTDEV and DSTDEVP Functions; Using the DSUM Function; Using the DVAR and DVARP Functions; Chapter 9: Using the Statistics Functions; Counting Items in a Data Set; Means, Modes, and Medians; Finding Values, Ranks, and Percentiles; Standard Deviations and Variances; Normal Distributions; t-distributions; f-distributions; Binomial Distributions; Chi-Square Distributions; Regression Analysis; Correlation; Some Really Esoteric Probability Distributions; Chapter 10: Descriptive Statistics Using the Descriptive Statistics ToolCreating a Histogram; Ranking by Percentile; Calculating Moving Averages; Exponential Smoothing; Generating Random Numbers; Sampling Data; Chapter 11: Inferential Statistics; Using the t-test Data Analysis Tool; Performing z-test Calculations; Creating a Scatter Plot; Using the Regression Data Analysis Tool; Using the Correlation Analysis Tool; Using the Covariance Analysis Tool; Using the ANOVA Data Analysis Tools; Creating an f-test Analysis; Using Fourier Analysis; Chapter 12: Optimization Modeling with Solver; Understanding Optimization Modeling Setting Up a Solver Worksheet |
| Record Nr. | UNINA-9910809370903321 |
|
Nelson Stephen L.
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||
| Hoboken, New Jersey : , : John Wiley & Sons, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Fundamentals of Supervised Machine Learning : With Applications in Python, R, and Stata / / by Giovanni Cerulli
| Fundamentals of Supervised Machine Learning : With Applications in Python, R, and Stata / / by Giovanni Cerulli |
| Autore | Cerulli Giovanni |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina |
519.50285
006.31 |
| Collana | Statistics and Computing |
| Soggetto topico |
Machine learning
Statistics - Computer programs Statistics Biometry Social sciences - Statistical methods Statistical Learning Machine Learning Statistical Software Statistics in Business, Management, Economics, Finance, Insurance Biostatistics Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Estadística Biometria |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-41337-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- The Ontology of Machine Learning -- The Statistics of Machine Learning -- Model Selection and Regularization -- Discriminant Analysis, Nearest Neighbor and Support Vector Machines -- Tree Modelling -- Artificial Neural Networks -- Deep Learning -- Sentiment Analysis -- Index. . |
| Record Nr. | UNINA-9910765481403321 |
|
Cerulli Giovanni
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Journal of statistical software
| Journal of statistical software |
| Pubbl/distr/stampa | [California], : Foundation for Open Access Statistics |
| Descrizione fisica | 1 online resource |
| Disciplina | 005 |
| Soggetto topico |
Statistics as Topic
Software Algorithms Statistics - Data processing Statistics - Computer programs |
| Soggetto genere / forma |
Periodical
Periodicals. |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | JSS |
| Record Nr. | UNINA-9910143050703321 |
| [California], : Foundation for Open Access Statistics | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
