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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

Material type
E-Book(소장)
Personal Author
Mailund, Thomas.
Title Statement
Functional data structures in R [electronic resource] : advanced statistical programming in R / Thomas Mailund.
Publication, Distribution, etc
Berkeley, CA :   Apress,   c2017.  
Physical Medium
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.
General Note
Title from e-Book title page.  
Bibliography, Etc. Note
Includes bibliographical references and index.
이용가능한 다른형태자료
Issued also as a book.  
Subject Added Entry-Topical Term
Computer science. Data structures (Computer science.).
Short cut
URL
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020 ▼a 9781484231432
020 ▼a 9781484231449 (e-book)
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100 1 ▼a Mailund, Thomas.
245 1 0 ▼a Functional data structures in R ▼h [electronic resource] : ▼b advanced statistical programming in R / ▼c Thomas Mailund.
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
945 ▼a KLPA
991 ▼a E-Book(소장)

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Main Library/e-Book Collection/ Call Number CR 005.11 Accession No. E14014941 Availability Loan can not(reference room) Due Date Make a Reservation Service M

Contents information

Table of Contents

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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