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Applied Statistical Learning [[electronic resource] ] : With Case Studies in Stata / / by Matthias Schonlau
| Applied Statistical Learning [[electronic resource] ] : With Case Studies in Stata / / by Matthias Schonlau |
| Autore | Schonlau Matthias <1967-> |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource |
| Disciplina | 519.50285 |
| Collana | Statistics and Computing |
| Soggetto topico |
Machine learning
Social sciences—Statistical methods Statistics Statistics—Computer programs Quantitative research Statistical Learning Machine Learning Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Statistics in Business, Management, Economics, Finance, Insurance Statistical Software Data Analysis and Big Data |
| ISBN | 3-031-33390-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- 1 Prologue -- 2 Statistical Learning: Concepts -- 3 Statistical Learning: Practical Aspects -- 4 Logistic Regression -- 5 Lasso and Friends -- 6 Working with Text Data -- 7 Nearest Neighbors -- 8 The Naive Bayes Classifier -- 9 Trees -- 10 Random Forests -- 11 Boosting -- 12 Support Vector Machines -- 13 Feature Engineering -- 14 Neural Networks -- 15 Stacking -- Index. |
| Record Nr. | UNINA-9910736996503321 |
Schonlau Matthias <1967->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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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 |
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Huang Changquan
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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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 |
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Huang Changquan
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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 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 | ||
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Computational Finance with R / / by Rituparna Sen, Sourish Das
| Computational Finance with R / / 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 |
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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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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 |
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Cerulli Giovanni
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Introduction to Statistics and Data Analysis [[electronic resource] ] : With Exercises, Solutions and Applications in R / / by Christian Heumann, Michael Schomaker, Shalabh
| Introduction to Statistics and Data Analysis [[electronic resource] ] : With Exercises, Solutions and Applications in R / / by Christian Heumann, Michael Schomaker, Shalabh |
| Autore | Heumann Christian <1962-> |
| Edizione | [2nd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (584 pages) |
| Disciplina | 330.015195 |
| Soggetto topico |
Statistics
Quantitative research Statistics—Computer programs Statistical Theory and Methods Data Analysis and Big Data Applied Statistics Statistical Software Estadística Econometria Macroeconomia R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-11833-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Descriptive Statistics: Introduction and Framework -- Frequency Measures and Graphical Representation of Data -- Measures of Central Tendency and Dispersion -- Association of Two Variables -- Part I Probability Calculus: Combinatorics -- Elements of Probability Theory -- Random Variables -- Probability Distributions -- Part III Inductive Statistics: Inference -- Hypothesis Testing -- Linear Regression -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries. |
| Record Nr. | UNISA-996508570303316 |
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Heumann Christian <1962->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Introduction to Statistics and Data Analysis : With Exercises, Solutions and Applications in R / / by Christian Heumann, Michael Schomaker, Shalabh
| Introduction to Statistics and Data Analysis : With Exercises, Solutions and Applications in R / / by Christian Heumann, Michael Schomaker, Shalabh |
| Autore | Heumann Christian <1962-> |
| Edizione | [2nd ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (584 pages) |
| Disciplina |
330.015195
519.5 |
| Soggetto topico |
Statistics
Quantitative research Statistics—Computer programs Statistical Theory and Methods Data Analysis and Big Data Applied Statistics Statistical Software Estadística Econometria Macroeconomia R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-11833-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I Descriptive Statistics: Introduction and Framework -- Frequency Measures and Graphical Representation of Data -- Measures of Central Tendency and Dispersion -- Association of Two Variables -- Part I Probability Calculus: Combinatorics -- Elements of Probability Theory -- Random Variables -- Probability Distributions -- Part III Inductive Statistics: Inference -- Hypothesis Testing -- Linear Regression -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries. |
| Record Nr. | UNINA-9910647396003321 |
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Heumann Christian <1962->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Partial Least Squares Path Modeling : Basic Concepts, Methodological Issues and Applications / / edited by Hengky Latan, Joseph F. Hair, Jr., Richard Noonan
| Partial Least Squares Path Modeling : Basic Concepts, Methodological Issues and Applications / / edited by Hengky Latan, Joseph F. Hair, Jr., Richard Noonan |
| Autore | Latan Hengky |
| Edizione | [2nd ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (495 pages) |
| Disciplina | 511.42 |
| Altri autori (Persone) |
HairJoseph F., Jr
NoonanRichard |
| Soggetto topico |
Statistics
Statistics - Computer programs Social sciences - Statistical methods Econometrics Multivariate analysis Statistical Theory and Methods Statistics in Business, Management, Economics, Finance, Insurance Statistical Software Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy Multivariate Analysis Anàlisi multivariable Econometria |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-37772-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction to the Partial Least Squares Path Modeling: Basic Concepts and Recent Methodological Enhancements -- Quantile Composite-Based Path Modeling with R: A Hands-On Guide -- Use of Partial Least Squares Path Modeling within and across Business Disciplines -- Statistical and Psychometric Properties of Three Weighting Schemes of the PLS-SEM Methodology -- Software Packages for Partial Least Squares Structural Equation Modeling: An Updated Review -- Revisiting and Extending PLS for Ordinal Measurement and Prediction -- Multicollinearity: An Overview and Introduction of Ridge PLS-SEM Estimation -- Demystifying Prediction in Mediation Research and the Use of Specific Indirect Effects and Indirect Effect Sizes -- Alternative Approaches to Higher-Order PLS-Path Modeling: A Discussion on Methodological Issues and Applications -- How to Apply Necessary Condition Analysis in PLS-SEM -- New Insights for Public Diplomacy Using PLS-SEM to Analyze the Polyphony of Voices: Value Drivers of the Country Image in Western European and BRICS countries -- To Survive or Not to Survive: Findings from PLS-SEM on the Relationship between Organizational Resources and Startups Survival -- Influence of Earnings Quality Dimensions on the Perception of Earnings Quality: An Empirical Application of Composite PLS using Archival Data -- Importance Performance Map Analysis of Capital Structure Using PLS-SEM: Evidence from Non-Financial Sector. |
| Record Nr. | UNINA-9910765478403321 |
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Latan Hengky
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Practicing R for Statistical Computing / / by Muhammad Aslam, Muhammad Imdad Ullah
| Practicing R for Statistical Computing / / by Muhammad Aslam, Muhammad Imdad Ullah |
| Autore | Aslam Muhammad |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (300 pages) |
| Disciplina | 005.55 |
| Altri autori (Persone) | Imdad UllahMuhammad |
| Soggetto topico |
Mathematical statistics—Data processing
Statistics—Computer programs Statistics and Computing Statistical Software R (Llenguatge de programació) Estadística Programari |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-9928-86-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. R Language: Introduction -- Chapter 2. Obtaining and Installing R Language -- Chapter 3. Using R as a Calculator -- Chapter 4. Data Mode and Data Structure -- Chapter 5. Working with Data -- Chapter 6. Descriptive Statistics -- Chapter 7. Probability and Probability Distributions -- Chapter 8. Confidence Intervals and Comparison Tests -- Chapter 9. Correlation & Regression Analysis -- Chapter 10. Graphing in R -- Chapter 11. Control Flow: election and Iteration -- Chapter 12. Functions and R Resources -- Chapter 13. Common Errors and Mistakes -- Chapter 14. Functions for Better Programming -- Chapter 15. Some Useful Functions -- Chapter 16. Important Packages. |
| Record Nr. | UNINA-9910735777603321 |
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Aslam Muhammad
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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