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Functional data structures in R [electronic resource] : advanced statistical programming in R

Functional data structures in R [electronic resource] : advanced statistical programming in R

자료유형
E-Book(소장)
개인저자
Mailund, Thomas.
서명 / 저자사항
Functional data structures in R [electronic resource] : advanced statistical programming in R / Thomas Mailund.
발행사항
Berkeley, CA :   Apress,   c2017.  
형태사항
1 online resource (xii, 256 p.) : ill.
ISBN
9781484231432 9781484231449 (e-book)
요약
Get 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.
일반주기
Title from e-Book title page.  
서지주기
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
일반주제명
Computer science. Data structures (Computer science.).
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260 ▼a Berkeley, CA : ▼b Apress, ▼c c2017.
300 ▼a 1 online resource (xii, 256 p.) : ▼b ill.
500 ▼a Title from e-Book title page.
504 ▼a Includes bibliographical references and index.
520 ▼a Get 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.
530 ▼a Issued also as a book.
538 ▼a Mode of access: World Wide Web.
650 0 ▼a Computer science.
650 0 ▼a Data structures (Computer science.).
856 4 0 ▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-1-4842-3144-9
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991 ▼a E-Book(소장)

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/e-Book 컬렉션/ 청구기호 CR 005.11 등록번호 E14014941 도서상태 대출불가(열람가능) 반납예정일 예약 서비스 M

컨텐츠정보

목차

CONTENTS
About the Author = vii
About the Technical Reviewer = ix
Introduction = xi
Chapter 1 Introduction = 1
Chapter 2 Abstract Data Structures = 3
 Structure on Data = 4
 Abstract Data Structures in R = 6
 Implementing Concrete Data Structures in R = 9
 Asymptotic Running Time = 11
 Experimental Evaluation of Algorithms = 15
Chapter 3 Immutable and Persistent Data = 25
 Persistent Data Structures = 26
 List Functions = 28
 Trees = 37
 Random Access Lists = 56
Chapter 4 Bags, Stacks, and Queues = 67
 Bags = 68
 Stacks = 73
 Queues = 74
  Side Effects Through Environments = 77
  Side Effects Through Closures = 79
  A Purely Functional Queue = 82
  Time Comparisons = 84
  Amortized Time Complexity and Persistent Data Structures = 85
  Double-Ended Queues = 87
 Lazy Queues = 95
  Implementing Lazy Evaluation = 96
  Lazy Lists = 98
  Amortized Constant Time, Logarithmic Worst-Case, Lazy Queues = 107
  Constant Time Lazy Queues = 118
  Explicit Rebuilding Queue = 124
Chapter 5 Heaps = 135
 Leftist Heaps = 140
 Binomial Heaps = 144
 Splay Heaps = 157
 Plotting Heaps = 178
 Heaps and Sorting = 183
Chapter 6 Sets and Search Trees = 189
 Search Trees = 190
 Red-Black Search Trees = 192
  Insertion = 195
  Deletion = 203
  Visualizing Red-Black Trees = 226
 Splay Trees = 231
Conclusions = 247
 Acknowledgements = 248
Bibliography = 249
Index = 251

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