Autore	Chapman Chris
Edizione	[1st ed. 2015.]
Pubbl/distr/stampa	Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Descrizione fisica	1 online resource (459 p.)
Disciplina	519.502855133
Collana	Use R!
Soggetto topico	Statistics Marketing R (Computer program language) Statistics for Business, Management, Economics, Finance, Insurance Statistics and Computing/Statistics Programs
ISBN	3-319-14436-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Welcome to R -- The R Language -- Describing Data -- Relationships Between Continuous Variables -- Comparing Groups: Tables and Visualizations -- Comparing Groups: Statistical Tests -- Identifying Drivers of Outcomes: Linear Models -- Reducing Data Complexity -- Additional Linear Modeling Topics -- Confirmatory Factor Analysis and Structural Equation Modeling -- Segmentation: Clustering and Classification -- Association Rules for Market Basket Analysis -- Choice Modeling -- Conclusion -- Appendix: R Versions and Related Software -- Appendix: Scaling up -- Appendix: Packages Used -- Index.
Record Nr.	UNINA-9910299777503321

Autore	Cornillon, Pierre-André
Pubbl/distr/stampa	Boca Raton : CRC Press, 2012
Descrizione fisica	xiv, 306 p. : ill. ; 24 cm
Disciplina	519.502855133
Soggetto non controllato	R
ISBN	978-1-4398-8145-3
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-990009616260403321

Autore	Lim Aloysius
Pubbl/distr/stampa	Birmingham, England : , : Packt Publishing, , 2015
Descrizione fisica	1 online resource (176 p.)
Disciplina	519.502855133
Collana	Community Experience Distilled
Soggetto topico	R (Computer program language)
Soggetto genere / forma	Electronic books.
ISBN	1-78398-927-0
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Understanding R's Performance - Why Are R Programs Sometimes Slow?; Three constraints on computing performance - CPU, RAM, and disk I/O; R is interpreted on the fly; R is single-threaded; R requires all data to be loaded into memory; Algorithm design affects time and space complexity; Summary; Chapter 2: Profiling - Measuring Code's Performance; Measuring the total execution time; Measuring execution time with system.time(); Repeating time measurements with rbenchmark Measuring distribution of execution time with microbenchmarkProfiling the execution time; Profiling a function with Rprof(); The profiling results; Profiling the memory utilization; Monitoring memory utilization, CPU utilization, and disk I/O using OS tools; Identifying and resolving bottlenecks; Summary; Chapter 3: Simple Tweaks to Make R Run Faster; Vectorization; Use of built-in functions; Preallocating memory; Use of simpler data structures; Use of hash tables for frequent lookups on large data; Seek fast alternative packages in CRAN; Summary Chapter 4: Using Compiled Code for Greater SpeedCompiling R code before execution; Compiling functions; Just-in-time (JIT) compilation of R code; Using compiled languages in R; Prerequisites; Including compiled code inline; Calling external compiled code; Considerations for using compiled code; The R APIs; R data types versus native data types; Creating R objects and garbage collection; Allocating memory for non-R objects; Summary; Chapter 5: Using GPUs to Run R Even Faster; General purpose computing on GPUs; R and GPUs; Installing gputools; Fast statistical modeling in R with gputools SummaryChapter 6: Simple Tweaks to Use Less RAM; Reusing objects without taking up more memory; Removing intermediate data when it is no longer needed; Calculating values on the fly instead of storing them persistently; Swapping active and non-active data; Summary; Chapter 7: Processing Large Datasets with Limited RAM; Using memory-efficient data structures; Smaller data types; Sparse matrices; Symmetric matrices; Bit vectors; Using memory-mapped files and processing data in chunks; The bigmemory package; The ff package; Summary; Chapter 8: Multiplying Performance with Parallel Computing Data parallelism versus task parallelismImplementing data parallel algorithms; Implementing task parallel algorithms; Running the same task on workers in a cluster; Running different tasks on workers in a cluster; Executing tasks in parallel on a cluster of computers; Shared memory versus distributed memory parallelism; Optimizing parallel performance; Summary; Chapter 9: Offloading Data Processing to Database Systems; Extracting data into R versus processing data in a database; Preprocessing data in a relational database using SQL; Converting R expressions into SQL; Using dplyr Using PivotalR
Record Nr.	UNINA-9910464102303321

Autore	Medeiros Kaelen
Edizione	[1st edition]
Pubbl/distr/stampa	Birmingham ; ; Mumbai : , : Packt, , [2018]
Descrizione fisica	1 online resource (202 pages)
Disciplina	519.502855133
Soggetto topico	R (Computer program language) Application software - Development
Soggetto genere / forma	Electronic books.
ISBN	1-78961-610-7
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Record Nr.	UNINA-9910493656103321

Autore	Tollefson Margot
Edizione	[2nd ed. 2019.]
Pubbl/distr/stampa	Berkeley, CA : , : Apress : , : Imprint : Apress, , 2019
Descrizione fisica	1 online resource (369 pages)
Disciplina	519.502855133
Soggetto topico	Programming languages (Electronic computers) Artificial intelligence Mathematical statistics Big data Computer programming R (Computer program language) Programming Languages, Compilers, Interpreters Artificial Intelligence Probability and Statistics in Computer Science Big Data Programming Techniques
ISBN	1-4842-4405-2
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Part 1: R Basics -- 1. Downloading R and Setting Up a File System -- 2. The R Prompt -- 3. Assignments and Operators -- Part 2: Kinds of Objects -- 4. Modes of Objects -- 5. Classes of Objects -- Part 3: Functions -- 6. Packaged Functions -- 7. User Created Functions -- 8. How to Use a Function -- Part 4: I/O and Manipulating Objects -- 9. Importing/Creating Data -- 10. Exporting from R -- 11. Descriptive Functions and Manipulating Objects -- Part 5: Flow control -- 12. Flow Control -- 13. Examples of Flow Control -- 14. The Functions ifelse() and switch() -- Part 6: Some Common Functions, Packages and Techniques -- 15. Some Common Functions -- 16. The Packages base, stats and graphics -- 17. The Tricks of the Trade.
Record Nr.	UNINA-9910338006103321