Autore	O'Gorman Thomas W
Edizione	[1st edition]
Pubbl/distr/stampa	Hoboken, N.J., : Wiley, 2012
Descrizione fisica	1 online resource (365 p.)
Disciplina	519.5/36
Soggetto topico	Regression analysis Computer adaptive testing R (Computer program language)
ISBN	1-280-58894-2 1-118-21825-6 9786613618771 1-118-21822-1
Classificazione	MAT029030
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Adaptive Tests of Significance Using Permutations of Residuals with R and SAS®; CONTENTS; Preface; 1 Introduction; 1.1 Why Use Adaptive Tests?; 1.2 A Brief History of Adaptive Tests; 1.2.1 Early Tests and Estimators; 1.2.2 Rank Tests; 1.2.3 The Weighted Least Squares Approach; 1.2.4 Recent Rank-Based Tests; 1.3 The Adaptive Test of Hogg, Fisher, and Randles; 1.3.1 Level of Significance of the HFR Test; 1.3.2 Comparison of Power of the HFR Test to the t Test; 1.4 Limitations of Rank-Based Tests; 1.5 The Adaptive Weighted Least Squares Approach; 1.5.1 Level of Significance 1.5.2 Comparison of Power of the Adaptive WLS Test to the t Test and the HFR Test1.6 Development of the Adaptive WLS Test; 2 Smoothing Methods and Normalizing Transformations; 2.1 Traditional Estimators of the Median and the Interquartile Range; 2.2 Percentile Estimators that Use the Smooth Cumulative Distribution Function; 2.2.1 Smoothing the Cumulative Distribution Function; 2.2.2 Using the Smoothed c.d.f. to Compute Percentiles; 2.2.3 R Code for Smoothing the c.d.f.; 2.2.4 R Code for Finding Percentiles; 2.3 Estimating the Bandwidth 2.3.1 An Estimator of Variability Based on Traditional Percentiles2.3.2 R Code for Finding the Bandwidth; 2.3.3 An Estimator of Variability Based on Percentiles from the Smoothed Distribution Function; 2.4 Normalizing Transformations; 2.4.1 Traditional Normalizing Methods; 2.4.2 Normalizing Data by Weighting; 2.5 The Weighting Algorithm; 2.5.1 An Example of the Weighing Procedure; 2.5.2 R Code for Weighting the Observations; 2.6 Computing the Bandwidth; 2.6.1 Error Distributions; 2.6.2 Measuring Errors in Adaptive Weighting; 2.6.3 Simulation Studies; 2.7 Examples of Transformed Data Exercises3 A Two-Sample Adaptive Test; 3.1 A Two-Sample Model; 3.2 Computing the Adaptive Weights; 3.2.1 R Code for Computing the Weights; 3.3 The Test Statistics for Adaptive Tests; 3.3.1 R Code to Compute the Test Statistic; 3.4 Permutation Methods for Two-Sample Tests; 3.4.1 Permutation of Observations; 3.4.2 Permutation of Residuals; 3.4.3 R Code for Permutations; 3.5 An Example of a Two-Sample Test; 3.6 R Code for the Two-Sample Test; 3.6.1 R Code for Computing the Test Statistics; 3.6.2 R Code to Compute the Traditional F Test Statistic and p-Value 3.6.3 An R Function that Computes the p-Value for the Adaptive Test3.6.4 R Code to Perform the Adaptive Test; 3.7 Level of Significance of the Adaptive Test; 3.8 Power of the Adaptive Test; 3.9 Sample Size Estimation; 3.10 A SAS Macro for the Adaptive Test; 3.11 Modifications for One-Tailed Tests; 3.12 Justification of the Weighting Method; 3.13 Comments on the Adaptive Two-sample Test; Exercises; 4 Permutation Tests with Linear Models; 4.1 Introduction; 4.2 Notation; 4.3 Permutations with Blocking; 4.4 Linear Models in Matrix Form; 4.5 Permutation Methods; 4.5.1 The Permute-Errors Method 4.5.2 The Permute-Residuals Method
Record Nr.	UNINA-9910141323703321

Autore	Stirrup Jen
Edizione	[1st edition]
Pubbl/distr/stampa	Birmingham : , : Packt, , 2017
Descrizione fisica	1 online resource (178 pages) : illustrations
Disciplina	658.4038011
Soggetto topico	R (Computer program language)
Soggetto genere / forma	Electronic books.
ISBN	1-5231-2523-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910467171903321

Autore	Rai Bharatendra
Edizione	[1st edition]
Pubbl/distr/stampa	Birmingham, England ; ; Mumbai : , : Packt, , [2019]
Descrizione fisica	1 online resource (vii, 337 pages) : illustrations
Disciplina	519.502855133
Soggetto topico	R (Computer program language)
ISBN	1-78953-498-4
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910793816103321

Autore	Mailund Thomas
Edizione	[1st ed. 2017.]
Pubbl/distr/stampa	Berkeley, CA : , : Apress : , : Imprint : Apress, , 2017
Descrizione fisica	1 online resource (XV, 110 p. 10 illus.)
Disciplina	005.11
Soggetto topico	Computer programming Programming languages (Electronic computers) Mathematical statistics R (Computer program language) Programming Techniques Programming Languages, Compilers, Interpreters Probability and Statistics in Computer Science
ISBN	9781484229194 1484229193
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	1. Classes and Generic Functions -- 2. Class Hierarchies -- 3. Implementation Reuse -- 4. Statistical Models -- 5. Operator Overloading -- 6. S4 Classes -- 7. R6 Classes -- 8. Conclusions.
Record Nr.	UNINA-9910254567203321

Autore	Latpate Raosaheb
Edizione	[1st ed. 2021.]
Pubbl/distr/stampa	Singapore : , : Springer, , [2021]
Descrizione fisica	1 online resource (XVII, 301 p. 23 illus., 13 illus. in color.)
Disciplina	519.52
Soggetto topico	Sampling (Statistics) R (Computer program language) Mostreig (Estadística)
Soggetto genere / forma	Llibres electrònics
ISBN	981-16-0622-6
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	-1. Introduction -- 2. Simple Random Sampling -- 3. Stratied Random Sampling -- 4. Cluster Sampling -- 5. Double Sampling -- 6. Probability Proportional to Size Sampling -- 7. Systematic Sampling -- 8. Resampling Techniques -- 9. Adaptive Cluster Sampling -- 10. Two-Stage Adaptive Cluster Sampling -- 11. Adaptive Cluster Double Sampling -- 12. Inverse Adaptive Cluster Sampling -- 13. Two Stage Inverse Adaptive Cluster Sampling -- 14. Stratified Inverse Adaptive Cluster Sampling -- 15. Negative Adaptive Cluster Sampling -- 16. Negative Adaptive Cluster Double Sampling -- 17. Two- Stage Negative Adaptive Cluster Sampling -- 18. Balanced and Unbalanced Ranked Set Sampling -- 19. Ranked Set Sampling in Other Parameter Estimation and Non-Parametric Inference -- 20. Important Versions of Ranked Set Sampling -- 21. Sampling Errors.
Record Nr.	UNISA-996466397403316