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Elementos básicos de estadística descriptiva para el análisis de datos / / Gabriel Jaime Posada Hernández
| Elementos básicos de estadística descriptiva para el análisis de datos / / Gabriel Jaime Posada Hernández |
| Autore | Posada Hernández Gabriel Jaime |
| Pubbl/distr/stampa | Medellín : , : Universidad Católica Luis Amigó, , 2016 |
| Descrizione fisica | 1 recurso en línea (156 páginas) |
| Disciplina | 519.502855369 |
| Soggetto topico |
Statistics - Data processing
Probabilities - Data processing Estadísticas - Proceso de datos Probabilidades - Proceso de datos |
| Soggetto genere / forma | Libros electronicos. |
| ISBN | 958-8943-05-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | spa |
| Record Nr. | UNINA-9910433231303321 |
Posada Hernández Gabriel Jaime
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| Medellín : , : Universidad Católica Luis Amigó, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Foundations of probabilistic programming / / edited by Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva [[electronic resource]]
| Foundations of probabilistic programming / / edited by Gilles Barthe, Joost-Pieter Katoen, Alexandra Silva [[electronic resource]] |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2021 |
| Descrizione fisica | 1 online resource (xiv, 568 pages) : digital, PDF file(s) |
| Disciplina | 001.642 |
| Soggetto topico |
Computer programming
Probabilities - Data processing |
| ISBN |
1-108-80574-4
1-108-77075-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910585962103321 |
| Cambridge : , : Cambridge University Press, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fundamental probability : a computational approach
| Fundamental probability : a computational approach |
| Autore | Paolella Marc S |
| Pubbl/distr/stampa | [Place of publication not identified], : John Wiley, 2006 |
| Disciplina | 519.2 |
| Soggetto topico |
Probabilities - Data processing
Mathematical Statistics Mathematics Physical Sciences & Mathematics |
| ISBN | 0-470-03535-8 |
| Classificazione | 31.70 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Combinatorics -- Probability spaces and counting -- Symmetric spaces and conditioning -- Univariate random variables -- Multivariate random variables -- Sums of random variables -- Continuous univariate random variables -- Joint and conditional random variables -- Multivariate transformations. |
| Record Nr. | UNINA-9910144722803321 |
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Paolella Marc S
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| [Place of publication not identified], : John Wiley, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fundamental probability : a computational approach
| Fundamental probability : a computational approach |
| Autore | Paolella Marc S |
| Pubbl/distr/stampa | [Place of publication not identified], : John Wiley, 2006 |
| Disciplina | 519.2 |
| Soggetto topico |
Probabilities - Data processing
Mathematical Statistics Mathematics Physical Sciences & Mathematics |
| ISBN | 0-470-03535-8 |
| Classificazione | 31.70 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Combinatorics -- Probability spaces and counting -- Symmetric spaces and conditioning -- Univariate random variables -- Multivariate random variables -- Sums of random variables -- Continuous univariate random variables -- Joint and conditional random variables -- Multivariate transformations. |
| Record Nr. | UNINA-9910830300903321 |
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Paolella Marc S
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| [Place of publication not identified], : John Wiley, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Fundamental probability : a computational approach
| Fundamental probability : a computational approach |
| Autore | Paolella Marc S |
| Pubbl/distr/stampa | [Place of publication not identified], : John Wiley, 2006 |
| Disciplina | 519.2 |
| Soggetto topico |
Probabilities - Data processing
Mathematical Statistics Mathematics Physical Sciences & Mathematics |
| ISBN | 0-470-03535-8 |
| Classificazione | 31.70 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Combinatorics -- Probability spaces and counting -- Symmetric spaces and conditioning -- Univariate random variables -- Multivariate random variables -- Sums of random variables -- Continuous univariate random variables -- Joint and conditional random variables -- Multivariate transformations. |
| Record Nr. | UNINA-9910841785203321 |
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Paolella Marc S
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| [Place of publication not identified], : John Wiley, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910460442103321 |
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Wan Shibiao
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| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto non controllato |
Bioinformatics
Computer Science Proteomics |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910797139603321 |
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Wan Shibiao
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| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak
| Machine learning for protein subcellular localization prediction / / Shibiao Wan, Man-Wai Mak |
| Autore | Wan Shibiao |
| Pubbl/distr/stampa | Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 |
| Descrizione fisica | 1 online resource (210 p.) |
| Disciplina | 572/.696 |
| Soggetto topico |
Proteins - Physiological transport - Data processing
Machine learning Probabilities - Data processing |
| Soggetto non controllato |
Bioinformatics
Computer Science Proteomics |
| ISBN |
1-5015-0150-X
1-5015-0152-6 |
| Classificazione | WC 7700 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front matter -- Preface -- Contents -- List of Abbreviations -- 1. Introduction -- 2. Overview of subcellular localization prediction -- 3. Legitimacy of using gene ontology information -- 4. Single-location protein subcellular localization -- 5. From single- to multi-location -- 6. Mining deeper on GO for protein subcellular localization -- 7. Ensemble random projection for large-scale predictions -- 8. Experimental setup -- 9. Results and analysis -- 10. Properties of the proposed predictors -- 11. Conclusions and future directions -- A. Webservers for protein subcellular localization -- B. Support vector machines -- C. Proof of no bias in LOOCV -- D. Derivatives for penalized logistic regression -- Bibliography -- Index |
| Record Nr. | UNINA-9910819391103321 |
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Wan Shibiao
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| Berlin, Germany ; ; Boston, Massachusetts : , : De Gruyter, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Probability and statistics with reliability, queuing, and computer science applications / / Kishor S. Trivedi, Duke University, Durham, North Carolina
| Probability and statistics with reliability, queuing, and computer science applications / / Kishor S. Trivedi, Duke University, Durham, North Carolina |
| Autore | Trivedi Kishor Shridharbhai <1946-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (991 p.) |
| Disciplina | 519.2 |
| Soggetto topico |
Probabilities - Data processing
Mathematical statistics - Data processing Computer algorithms Engineering mathematics |
| ISBN |
1-119-31420-8
0-471-46081-8 1-119-28544-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910135014603321 |
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Trivedi Kishor Shridharbhai <1946->
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| Hoboken, New Jersey : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Probability with applications and R / / Amy S. Wagaman, Robert P. Dobrow
| Probability with applications and R / / Amy S. Wagaman, Robert P. Dobrow |
| Autore | Wagaman Amy S. <1982-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , [2021] |
| Descrizione fisica | 1 online resource (547 pages) |
| Disciplina | 519.502855133 |
| Soggetto topico |
Probabilities - Data processing
Probabilities R (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-5231-4377-0
1-119-69241-5 1-119-69243-1 1-119-69234-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Preface -- Acknowledgments -- About the Companion Website -- Introduction -- Chapter 1 First Principles -- 1.1 Random Experiment, Sample Space, Event -- 1.2 What Is a Probability? -- 1.3 Probability Function -- 1.4 Properties of Probabilities -- 1.5 Equally likely outcomes -- 1.6 Counting I -- 1.6.1 Permutations -- 1.7 Counting II -- 1.7.1 Combinations and Binomial Coefficients -- 1.8 Problem‐Solving Strategies: Complements and Inclusion-Exclusion -- 1.9 A First Look at Simulation -- 1.10 Summary -- Exercises -- Chapter 2 Conditional Probability and Independence -- 2.1 Conditional Probability -- 2.2 New Information Changes the Sample Space -- 2.3 Finding P(A and B) -- 2.3.1 Birthday Problem -- 2.4 Conditioning and the Law of Total Probability -- 2.5 Bayes Formula and Inverting a Conditional Probability -- 2.6 Independence and Dependence -- 2.7 Product Spaces* -- 2.8 Summary -- Exercises -- Chapter 3 INTRODUCTION TO DISCRETE RANDOM VARIABLES -- Learning Outcomes -- 3.1 Random Variables -- 3.2 Independent Random Variables -- 3.3 Bernoulli Sequences -- 3.4 Binomial Distribution -- 3.5 Poisson Distribution -- 3.5.1 Poisson Approximation of Binomial Distribution -- 3.5.2 Poisson as Limit of Binomial Probabilities* -- 3.6 Summary -- Exercises -- Chapter 4 Expectation and More with Discrete Random Variables -- 4.1 Expectation -- 4.2 Functions of Random Variables -- 4.3 Joint distributions -- 4.4 Independent Random Variables -- 4.4.1 Sums of Independent Random Variables -- 4.5 Linearity of expectation -- 4.6 Variance and Standard Deviation -- 4.7 Covariance and Correlation -- 4.8 Conditional Distribution -- 4.8.1 Introduction to Conditional Expectation -- 4.9 Properties of Covariance and Correlation* -- 4.10 Expectation of a Function of a Random Variable* -- 4.11 Summary -- Exercises.
Chapter 5 More Discrete Distributions and Their Relationships -- 5.1 Geometric Distribution -- 5.1.1 Memorylessness -- 5.1.2 Coupon Collecting and Tiger Counting -- 5.2 Moment‐Generating Functions -- 5.3 Negative Binomial-Up from the Geometric -- 5.4 Hypergeometric-Sampling Without Replacement -- 5.5 From Binomial to Multinomial -- 5.6 Benford's Law* -- 5.7 Summary -- Exercises -- Chapter 6 Continuous Probability -- 6.1 Probability Density Function -- 6.2 Cumulative Distribution Function -- 6.3 Expectation and Variance -- 6.4 Uniform Distribution -- 6.5 Exponential Distribution -- 6.5.1 Memorylessness -- 6.6 Joint Distributions -- 6.7 Independence -- 6.7.1 Accept-Reject Method -- 6.8 Covariance, Correlation -- 6.9 Summary -- Exercises -- Chapter 7 Continuous Distributions -- 7.1 Normal Distribution -- 7.1.1 Standard Normal Distribution -- 7.1.2 Normal Approximation of Binomial Distribution -- 7.1.3 Quantiles -- 7.1.4 Sums of Independent Normals -- 7.2 Gamma Distribution -- 7.2.1 Probability as a Technique of Integration -- 7.3 Poisson Process -- 7.4 Beta Distribution -- 7.5 Pareto Distribution* -- 7.6 Summary -- Exercises -- Chapter 8 Densities of Functions of Random Variables -- 8.1 Densities via CDFs -- 8.1.1 Simulating a Continuous Random Variable -- 8.1.2 Method of Transformations -- 8.2 Maximums, Minimums, and Order Statistics -- 8.3 Convolution -- 8.4 Geometric Probability -- 8.5 Transformations of Two Random Variables* -- 8.6 Summary -- Exercises -- Chapter 9 Conditional Distribution, Expectation, and Variance -- 9.1 Conditional Distributions -- 9.2 DISCRETE AND CONTINUOUS: MIXING IT UP -- 9.3 CONDITIONAL EXPECTATION -- 9.3.1 From Function to Random Variable -- 9.3.2 Random Sum of Random Variables -- 9.4 COMPUTING PROBABILITIES BY CONDITIONING -- 9.5 CONDITIONAL VARIANCE -- 9.6 BIVARIATE NORMAL DISTRIBUTION* -- 9.7 SUMMARY -- Exercises. Chapter 10 Limits -- 10.1 WEAK LAW OF LARGE NUMBERS -- 10.1.1 Markov and Chebyshev Inequalities -- 10.2 STRONG LAW OF LARGE NUMBERS -- 10.3 METHOD OF MOMENTS* -- 10.4 MONTE CARLO INTEGRATION -- 10.5 CENTRAL LIMIT THEOREM -- 10.5.1 Central Limit Theorem and Monte Carlo -- 10.6 A PROOF OF THE CENTRAL LIMIT THEOREM -- 10.7 SUMMARY -- Exercises -- Chapter 11 Beyond Random Walks And Markov Chains -- 11.1 RANDOM WALKS ON GRAPHS -- 11.1.1 Long‐Term Behavior -- 11.2 RANDOM WALKS ON WEIGHTED GRAPHS AND MARKOV CHAINS -- 11.2.1 Stationary Distribution -- 11.3 FROM MARKOV CHAIN TO MARKOV CHAIN MONTE CARLO -- 11.4 SUMMARY -- Exercises -- Chapter A Probability Distributions in R -- Chapter B Summary of Probability Distributions -- Chapter C Mathematical Reminders -- Chapter D Working with Joint Distributions -- SOLUTIONS TO EXERCISES -- References -- Index -- EULA. |
| Record Nr. | UNINA-9910555264603321 |
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Wagaman Amy S. <1982->
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| Hoboken, New Jersey : , : Wiley, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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