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010   $a9781484231449
010   $a1484231449
024 7 $a10.1007/978-1-4842-3144-9
035   $a(CKB)4100000001041910
035   $a(DE-He213)978-1-4842-3144-9
035   $a(MiAaPQ)EBC5150667
035   $a(CaSebORM)9781484231449
035   $a(PPN)221255664
035   $a(OCoLC)1076922679
035   $a(OCoLC)on1076922679
035   $a(EXLCZ)994100000001041910
100   $a20171117d2017      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aFunctional data structures in R $eadvanced statistical programming in R /$fby Thomas Mailund
205   $a1st ed. 2017.
210  1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2017.
215   $a1 online resource (XII, 256 p. 57 illus., 2 illus. in color.)
311 08$a9781484231432 
311 08$a1484231430 
320   $aIncludes bibliographical references and index.
330   $aGet an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you?ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You?ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You?ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R. By the end of Functional Data Structures in R, you?ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications. You will: Carry out algorithmic programming in R  Use abstract data structures  Work with both immutable and persistent data  Emulate pointers and implement traditional data structures in R Implement data structures in C/C++ with some wrapper code in R Build new versions of traditional data structures that are known.
517 3 $aAdvanced statistical programming in R
606   $aComputer programming
606   $aData structures (Computer science)
606   $aProgramming languages (Electronic computers)
606   $aMathematical statistics
606   $aR (Computer program language)
606   $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010
606   $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017
606   $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037
606   $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036
615  0$aComputer programming.
615  0$aData structures (Computer science)
615  0$aProgramming languages (Electronic computers)
615  0$aMathematical statistics.
615  0$aR (Computer program language)
615 14$aProgramming Techniques.
615 24$aData Structures.
615 24$aProgramming Languages, Compilers, Interpreters.
615 24$aProbability and Statistics in Computer Science.
676   $a005.11
700   $aMailund$b Thomas$4aut$4http://id.loc.gov/vocabulary/relators/aut$0846442
801  0$bUMI
801  1$bUMI
906   $aBOOK
912   $a9910254852603321
996   $aFunctional Data Structures in R$92056107
997   $aUNINA