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Applied Statistics and Multivariate Data Analysis for Business and Economics [[electronic resource] ] : A Modern Approach Using SPSS, Stata, and Excel / / by Thomas Cleff
| Applied Statistics and Multivariate Data Analysis for Business and Economics [[electronic resource] ] : A Modern Approach Using SPSS, Stata, and Excel / / by Thomas Cleff |
| Autore | Cleff Thomas |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XXIII, 474 p. 269 illus., 110 illus. in color.) |
| Disciplina | 519.535 |
| Soggetto topico |
Econometrics
Big data Statistics Big Data/Analytics Statistics for Business, Management, Economics, Finance, Insurance Statistics for Social Sciences, Humanities, Law Statistics and Computing/Statistics Programs Econometria Anàlisi multivariable Estadística econòmica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-17767-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Statistics and Empirical Research -- From Disarray to Dataset -- Univariate Data Analysis -- Bivariate Association -- Classical Measurement Theory.-Calculating Probability -- Random Variables and Probability Distributions -- Parameter Estimation -- Hypothesis Testing -- Regression Analysis -- Time Series and Indices -- Cluster Analysis -- Factor Analysis. |
| Record Nr. | UNINA-9910349537003321 |
Cleff Thomas
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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 Statistics for Business and Management using Microsoft Excel [[electronic resource] /] / by Linda Herkenhoff, John Fogli
| Applied Statistics for Business and Management using Microsoft Excel [[electronic resource] /] / by Linda Herkenhoff, John Fogli |
| Autore | Herkenhoff Linda |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XIV, 417 p. 620 illus., 569 illus. in color.) |
| Disciplina | 330.015195 |
| Soggetto topico |
Statistics
Statistics and Computing/Statistics Programs Statistics for Business, Management, Economics, Finance, Insurance Statistics, general |
| ISBN | 1-4614-8423-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Data and Statistics -- Key Concepts -- Discussion -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 2: Introduction to Excel and Basic Charts -- Key Concepts -- Discussion -- Basic Concepts -- Start Up -- Adding Data Analysis Toolpak -- Excel Elements -- Entering Formulas -- Cell References -- Sorting Data -- Filtering Data -- Getting Excel Help -- Statistical Tools -- Predefined or Built-In Formulas -- Formatting Data -- Chart Wizard -- Formatting of Graphs -- Bar and Column Charts -- Pie Charts -- Line Charts and Area Charts -- Line Graph Example -- Area Chart Example -- Other Charts -- Bubble Chart -- Radar Chart -- PivotTables (Aka Crosstabs) -- Excel -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 3: Summarizing Data: Descriptive Statistics and Histograms -- Key Concepts -- Discussion -- Symbols -- The Histogram -- Excel -- Descriptive Statistics -- Descriptive Output Results -- Changing the Width of the Column Output -- Using Excel Functions -- Histograms -- Example Problem -- Setting Up the Bin Ranges -- Creating the Histogram Chart -- Histogram Clean Up -- Closing Gaps Between Bars -- Change Labels on x-axis -- Removing More from the Chart and Labeling the Last Column -- Remove Legend -- Axes Labels -- Moving Axes Labels -- Changing the Bar Color -- Changing Chart Title -- Changing Chart Background Fill -- Rotating the y-axis Label from Vertical to Horizontal -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 4: Normal Distributions.
Key Concepts -- Discussion -- Excel -- Outline placeholder -- 1. Percentile Calculation Problems (NORM.DIST) -- (a) Calculating the area to the left of a value -- What % of the Time Did You Deliver to Less Than () 90 Stores During Last December and January? In Other Words How Much Data Is... -- (b) Calculating the area between 2 values -- What % of the Time Did You Deliver Fire Logs to Between 90 and 120 Stores During Last December and January? -- (c) Calculating the area to the right of a value -- What % of Time Did You Deliver to 130 or More Stores ( \geq ) During Last December and January? In Other Words How Much Da... -- (d) Graphing a normal distribution (Area Graph) -- Step 1 -- Step 2 -- Step 3 -- 2. Converting Percentiles to Measured Units (NORM.INV) -- Calculate the Number of Stores Corresponding with the 99th Percentile -- 3. Converting Measured Units to z-Scores (STANDARDIZE) -- Convert the Measured Value of 135 Stores to a z-Score -- 4. Calculate Rank and Percentile (Rank and Percentile) -- Outline placeholder -- Output -- 5. Non-normal Distributions -- Calculate What Percentage of Rents Fall Between 409 and 573 -- Step 1: Convert the Measured Values to Standard Units -- Step 2: Use Chebyshev Approximation=1-(1/(k)2) where k is the boundary value in standard units -- Common Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 5: Survey Design -- Key Concepts -- Discussion -- Basic Concepts -- Survey Design -- Scale -- Types of Questions -- Single Response/Select -- Multiple Response/Select -- Structured Questions -- Ranking and Rating -- Non-structured (Open-Ended) Questions -- Data -- Labels -- Demographic Data -- Response Rates -- Editing: Data Quality -- Coding -- Errors in Survey Question Creation -- Loaded Questions. Leading Questions -- Double-Barreled Questions -- Errors in Survey Data Collection -- Random Sampling Error -- Systematic Error -- Response Bias -- Checklist -- Excel -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 6: Sampling -- Key Concepts -- Discussion -- Types of Problems -- Mean versus proportion problems require slightly different treatment -- Finite versus infinite population size is another important factor in determining the appropriate sample size -- Rules of thumb -- Excel -- Problem Type: Infinite Mean -- Practice Problem for Infinite Mean -- Problem Type: Infinite Proportion -- Practice Problem for Infinite Proportion -- Finite Population Correction Factor (fpc) -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 7: Inference -- Key Concepts -- Discussion -- Inferring Proportions -- Example Problem -- Excel -- Inferring Averages -- Example Problem -- Excel -- Confidence Intervals with Proportion Inference -- Example Problem -- Excel -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 8: Probability -- Key Concepts -- Discussion -- Example 1 -- Example 2 -- Excel -- Finding Probabilities Using Normal Distributions -- What Is the Probability That a Dealership Will Sell 90 Cars or Less (x90) per Week? -- What Is the Probability That a Car Dealership Will Sell at least 130 (x130) Cars per Week? -- What Is the Probability That a Car Dealership Will Sell Between 90 and 120 Cars per Week? -- Calculating Combinations and Permutations -- Permutation -- Combination -- Finding Probabilities Using the Binomial Distribution. Royal Bank Retention Problem -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 9: Correlation -- Key Concepts -- Discussion -- Nonlinear data caution -- Average data caution -- Excel -- Correlation: One r Value or Correlation Matrix -- Method 1: Two or More Data Sets (Matrix) -- Method 2: Only 2 Data Sets -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 10: Simple Linear Regression -- Key Concepts -- Discussion -- Residuals and Tests for Linearity -- Standardized Residuals and Outliers -- Excel -- Scatterplot: Compute the Regression Line and the Coefficient of Determination -- Regression Function: Compute the Regression Model -- Compute Residual Plots Using the Regression Function -- Using Excel´s Regression Tool to Test for Normality of the Distribution of Residuals -- Method 1: Normal Probability Plot -- Method 2: Normal Distribution of Residuals -- Using Excel´s Regression Tool to Test for Constant Variance of Residuals -- Summary of Regression Analysis Process -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems -- Discussion Boards -- Group Activities -- Parting Thought -- Problem Solutions -- Chapter 11: Significance Tests Part 1 -- Key Concepts -- Discussion -- Basic Concepts -- Choosing the Appropriate Significance Test -- One-Tailed Tests -- Two-Tailed Tests -- Significance Tests -- F-test -- Basic Descriptions of F-Test Applications -- Example 1: One-Way Repeated Measures Using ANOVA -- Example 2: Regression Problems -- Example 3: F-Test for Equality of Two Variances -- Example 4: Between Group ANOVA -- Excel -- Example 1: One-Way Repeated Measures Using ANOVA. Example 2: Regression -- Example 3: Two Sample for Variances -- One-Tailed F-Test for Two Sample for Variances -- Two-Tailed F-Test for Equality of Two Variances -- Example 4: Between Group ANOVA -- One-Tail F-Test Between Group ANOVA -- Two-Tail F-Test Between Group ANOVA -- t-Test -- Basic Descriptions of t-Test Applications -- Example 1: Regression Problems -- Example 2: t-Test for Equality of Means -- Example 3: t-TEST Paired Samples -- Excel -- Example 1: Regression Problems -- Example 2: t-Test for Equality of Means -- One-Tailed Test -- Two-Tailed Test -- Example 3: Before-After Models -- One-Tailed Test -- Two-Tailed Test -- T.TEST -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 12: Significance Tests Part 2 -- Key Concepts -- Discussion -- Significance Tests -- X2 Test -- Example 1: Goodness-of-Fit Test -- Example 2: Independence of Two Variables -- Excel -- Example 1: Goodness of Fit -- Example 2: Testing Independence -- z-Test -- Excel -- Example 1: Z-Test One Sample Mean Versus a Standard -- One-Tailed Results -- Two-Tailed Results -- Example 2: Testing the Means of Two Populations -- Z.TEST Tool for Comparing a Mean or Proportion with a Standard -- Example Problem -- Common Excel Pitfalls -- Final Thoughts and Activities -- Practice Problems and Case Studies -- Discussion Boards -- Group Activity -- Parting Thought -- Problem Solutions -- Chapter 13: Multiple Regression -- Key Concepts -- Discussion -- Excel -- Step 1: Fit the Model with Selected Independent Variables -- Step 2: Does Multicollinearity Exist? Run a Correlation Matrix -- Step 3: Run Regression Model -- Step 4: Are the Assumptions of Regression Satisfied? -- Step 5: Test Overall Model Significance (F-Test). Step 6: Check p-Values for Independent Variables Meet Significance Criteria (t-Test). |
| Record Nr. | UNINA-9910437878003321 |
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Herkenhoff Linda
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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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Astrostatistical Challenges for the New Astronomy [[electronic resource] /] / edited by Joseph M. Hilbe
| Astrostatistical Challenges for the New Astronomy [[electronic resource] /] / edited by Joseph M. Hilbe |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (246 p.) |
| Disciplina | 520.15195 |
| Collana | Springer Series in Astrostatistics |
| Soggetto topico |
Statistics
Astronomy Astrophysics Statistical Theory and Methods Statistics and Computing/Statistics Programs Astronomy, Astrophysics and Cosmology |
| ISBN |
1-283-90970-7
1-4614-3508-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Joseph Hilbe, Jet Propulsion Laboratory and Arizona State University, Astrostatistics: A brief history and view to the future -- Thomas Loredo, Cornell Univ, Bayesian astrostatistics: A backward look to the future -- Stefano Andreon, INAF-Osservatorio Astronomico di Brera, Italy, Understanding better (some) astronomical data using Bayesian methods -- Martin Kunz, Institute for Theoretical Physics, Univ of Geneva, BEAMS: separating the wheat from the chaff in supernova analysis -- Benjamin Wandelt, Institut d'Astrophysique de Paris, Université Pierre et Marie Curie, France, Cosmostatistics -- Roberto Trotta, Astrophysics Group, Dept of Physics, Imperial College London (with Farhan Feroz (Cambridge), Mike Hobson (Cambridge), and Roberto Ruiz de Austri (Univ of Valencia, Spain), Recent advances in Bayesian inference in cosmology and astroparticle physics thanks to the Multinest Algorithm -- Phillip Gregory, Department of Astronomy, Univ of British Columbia, Canada, Extrasolar planets via Bayesian model fitting -- Marc Henrion, Dept of Mathematics, Imperial College, London, UK (with Daniel Mortlock (Imperial), Axel Gandy (Imperial), and David J. Hand (Imperial)), Subspace methods for anomaly detection in high dimensional astronomical databases -- Asis Kumar Chattopadhyay, Dept of Statistics, Univ of Calcutta, India (with Tanuka Chattyopadhyay, Tuli De, and Saptarshi Mondal), Independent Component Analysis for dimension reduction classification: Hough transform and CASH Algorithm -- Marisa March, Astrophysics Group, Dept of Physics, Imperial College London (with Roberto Trotta), Improved cosmological constraints from a Bayesian hierarchical model of supernova type Ia data . |
| Record Nr. | UNINA-9910437862903321 |
| New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Asymmetric Kernel Smoothing [[electronic resource] ] : Theory and Applications in Economics and Finance / / by Masayuki Hirukawa
| Asymmetric Kernel Smoothing [[electronic resource] ] : Theory and Applications in Economics and Finance / / by Masayuki Hirukawa |
| Autore | Hirukawa Masayuki |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 110 p. 5 illus.) |
| Disciplina | 519.5 |
| Collana | JSS Research Series in Statistics |
| Soggetto topico |
Statistics
Statistics for Business, Management, Economics, Finance, Insurance Statistical Theory and Methods Statistics for Social Sciences, Humanities, Law Statistics and Computing/Statistics Programs |
| ISBN | 981-10-5466-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Asymmetric kernels: definition and history -- 2. Density estimation from nonnegative observations -- 3. Regression estimation with nonnegative regressors -- 4. Model specification tests -- 5. Asymmetric kernel smoothing in action: applications in economics and finance. |
| Record Nr. | UNINA-9910300124103321 |
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Hirukawa Masayuki
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| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Basic Elements of Computational Statistics [[electronic resource] /] / by Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin
| Basic Elements of Computational Statistics [[electronic resource] /] / by Wolfgang Karl Härdle, Ostap Okhrin, Yarema Okhrin |
| Autore | Härdle Wolfgang Karl |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XXI, 305 p. 97 illus., 66 illus. in color.) |
| Disciplina | 519.50285 |
| Collana | Statistics and Computing |
| Soggetto topico |
Statistics
Mathematical statistics Biostatistics Statistics and Computing/Statistics Programs Statistical Theory and Methods Probability and Statistics in Computer Science Statistics for Business, Management, Economics, Finance, Insurance Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
| ISBN | 3-319-55336-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The Basics of R -- Numerical Techniques -- Combinatorics and Discrete Distributions -- Univariate Distributions -- Univariate Statistical Analysis -- Basic Nonparametric Methods -- Multivariate Distributions -- Multivariate Statistical Analysis -- Random Numbers in R -- Advanced Graphical Techniques in R -- Symbols and Notations. |
| Record Nr. | UNINA-9910254309603321 |
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Härdle Wolfgang Karl
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian cost-effectiveness analysis with the R package BCEA [[electronic resource] /] / by Gianluca Baio, Andrea Berardi, Anna Heath
| Bayesian cost-effectiveness analysis with the R package BCEA [[electronic resource] /] / by Gianluca Baio, Andrea Berardi, Anna Heath |
| Autore | Baio Gianluca |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XVI, 168 p. 55 illus., 26 illus. in color.) |
| Disciplina | 519.542 |
| Collana | Use R! |
| Soggetto topico |
Statistics
Health economics Health informatics Practice of medicine R (Computer program language) Statistics for Life Sciences, Medicine, Health Sciences Health Economics Statistics and Computing/Statistics Programs Health Informatics Statistics for Business, Management, Economics, Finance, Insurance Practice and Hospital Management |
| ISBN | 3-319-55718-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Bayesian analysis in health economics -- Case studies -- BCEA — a R package for Bayesian cost-effectiveness analysis -- Probabilistic sensitivity analysis using BCEA -- BCEAweb: a user-friendly web-app to use BCEA. |
| Record Nr. | UNINA-9910254283503321 |
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Baio Gianluca
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Essentials with R [[electronic resource] /] / by Jean-Michel Marin, Christian P. Robert
| Bayesian Essentials with R [[electronic resource] /] / by Jean-Michel Marin, Christian P. Robert |
| Autore | Marin Jean-Michel |
| Edizione | [2nd ed. 2014.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (XIV, 296 p. 75 illus., 38 illus. in color.) |
| Disciplina | 519.5 |
| Collana | Springer Texts in Statistics |
| Soggetto topico |
Statistics
R (Computer program language) Statistics and Computing/Statistics Programs Statistical Theory and Methods |
| ISBN | 1-4614-8687-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | User's Manual -- Normal Models -- Regression and Variable Selection -- Generalized Linear Models -- Capture-Recapture Experiments -- Mixture Models -- Time Series -- Image Analysis -- References -- Index. |
| Record Nr. | UNINA-9910300148603321 |
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Marin Jean-Michel
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| New York, NY : , : Springer New York : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis [[electronic resource] /] / by Uffe B. Kjærulff, Anders L. Madsen
| Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis [[electronic resource] /] / by Uffe B. Kjærulff, Anders L. Madsen |
| Autore | Kjærulff Uffe B |
| Edizione | [2nd ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (387 p.) |
| Disciplina | 003.54 |
| Collana | Information Science and Statistics |
| Soggetto topico |
Statistics
Mathematical statistics Data mining Artificial intelligence Operations research Management science Probabilities Statistics and Computing/Statistics Programs Probability and Statistics in Computer Science Data Mining and Knowledge Discovery Artificial Intelligence Operations Research, Management Science Probability Theory and Stochastic Processes |
| ISBN |
1-283-86506-8
1-4614-5104-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Networks -- Probabilities -- Probabilistic Networks -- Solving Probabilistic Networks -- Eliciting the Model -- Modeling Techniques -- Data-Driven Modeling -- Conflict Analysis -- Sensitivity Analysis -- Value of Information Analysis -- Quick Reference to Model Construction -- List of Examples -- List of Figures -- List of Tables -- List of Symbols -- References -- Index. |
| Record Nr. | UNINA-9910437602803321 |
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Kjærulff Uffe B
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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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Bayesian Networks in R [[electronic resource] ] : with Applications in Systems Biology / / by Radhakrishnan Nagarajan, Marco Scutari, Sophie Lèbre
| Bayesian Networks in R [[electronic resource] ] : with Applications in Systems Biology / / by Radhakrishnan Nagarajan, Marco Scutari, Sophie Lèbre |
| Autore | Nagarajan Radhakrishnan |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (168 p.) |
| Disciplina | 519.542 |
| Collana | Use R! |
| Soggetto topico |
Statistics
Programming languages (Electronic computers) R (Computer program language) Statistics and Computing/Statistics Programs Statistical Theory and Methods Programming Languages, Compilers, Interpreters |
| ISBN | 1-4614-6446-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Bayesian Networks in the Absence of Temporal Information -- Bayesian Networds in the Presence of Temporal Information -- Bayesian Network Inference Algorithms -- Parallel Computing for Bayesian Networks -- Solutions -- Index -- References. |
| Record Nr. | UNINA-9910438136003321 |
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Nagarajan Radhakrishnan
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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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Bayesian nonparametric data analysis [[electronic resource] /] / by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson
| Bayesian nonparametric data analysis [[electronic resource] /] / by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson |
| Autore | Müller Peter |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (203 p.) |
| Disciplina | 519.542 |
| Collana | Springer Series in Statistics |
| Soggetto topico |
Statistics
Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Life Sciences, Medicine, Health Sciences |
| ISBN | 3-319-18968-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Acronyms -- 1.Introduction -- 2.Density Estimation - DP Models -- 3.Density Estimation - Models Beyond the DP -- 4.Regression -- 5.Categorical Data -- 6.Survival Analysis -- 7.Hierarchical Models -- 8.Clustering and Feature Allocation -- 9.Other Inference Problems and Conclusions -- Appendix: DP package. |
| Record Nr. | UNINA-9910299766803321 |
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Müller Peter
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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