R data structures and algorithms : increase speed and performance of your applications with efficient data structures and algorithms

R data structures and algorithms increase speed and performance of your applications with efficient data structures and algorithms

Increase speed and performance of your applications with efficient data structures and algorithms About This Book See how to use data structures such as arrays, stacks, trees, lists, and graphs through real-world examples Find out about important and advanced data structures such as searching and so...

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Detalles Bibliográficos
Otros Autores: Prakash, PKS, author (author), Rao, Achyutuni Sri Krishna, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England ; Mumbai, [India] : Packt Publishing 2016.
Edición:1st edition
Materias:
R (Computer program language)
Data structures (Computer science)
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630303606719
Tabla de Contenidos:
  • Cover
  • Copyright
  • Credits
  • About the Authors
  • Acknowledgments
  • About the Reviewer
  • www.PacktPub.com
  • Table of Contents
  • Preface
  • Chapter 1: Getting Started
  • Introduction to data structure
  • Abstract data type and data structure
  • Relationship between problem and algorithm
  • Basics of R
  • Installation of R
  • Basic data types in R
  • Operations in R
  • Control structures in R
  • If condition
  • If…else condition
  • Ifelse function
  • For() loop
  • Nested for( ) loop
  • While loop
  • Special statements in loops
  • Break statement
  • Next statement
  • Repeat loop
  • First class functions in R
  • Exercises
  • Summary
  • Chapter 2: Algorithm Analysis
  • Getting started with data structure
  • Memory management in R
  • System runtime in R
  • Best, worst, and average cases
  • Computer versus algorithm
  • Algorithm asymptotic analysis
  • Upper bounds or Big O notation
  • Lower bounds or Big Omega notation (Ω)
  • Big θ notation
  • Simplifying rules
  • Classifying rules
  • Computation evaluation of a program
  • Component 1 - Assignment operator
  • Component 2 - Simple loop
  • Component 3 - Complex loop
  • Component 4 - Loops with conditional statements
  • Component 5 - Recursive statements
  • Analyzing problems
  • Space bounds
  • Exercises
  • Summary
  • Chapter 3: Linked Lists
  • Data types in R
  • Vector and atomic vector
  • Element data types
  • Factor
  • Matrix
  • Array
  • Dataframes
  • List
  • Object-oriented programming using R
  • Linked list
  • Linear linked list
  • Doubly linked list
  • Circular linked list
  • Array-based list
  • Analysis of list operations
  • Exercises
  • Summary
  • Chapter 4: Stacks and Queues
  • Stacks
  • Array-based stacks
  • Linked stacks
  • Comparison of array-based and linked stacks
  • Implementing recursion
  • Queues
  • Array-based queues
  • Linked queues
  • Comparison of array-based and linked queues.
  • Dictionaries
  • Exercises
  • Summary
  • Chapter 5: Sorting Algorithms
  • Sorting terminology and notation
  • Three Θ(n²) sorting algorithms
  • Insertion sort
  • Bubble sort
  • Selection sort
  • The cost of exchange sorting
  • Shell sort
  • Merge sort
  • Quick sort
  • Heap sort
  • Bin sort and radix sort
  • An empirical comparison of sorting algorithms
  • Lower bounds for sorting
  • Exercises
  • Summary
  • Chapter 6: Exploring Search Options
  • Searching unsorted and sorted vectors
  • Self-organizing lists
  • Heuristic 1 - Count
  • Heuristic 2 - Move-to-front
  • Heuristic 3 - Transpose
  • Hashing
  • Hash functions
  • Open hashing
  • Closed hashing
  • Bucket hashing
  • Linear probing
  • Analysis of closed hashing
  • Deletion
  • Exercises
  • Summary
  • Chapter 7: Indexing
  • Linear indexing
  • ISAM
  • Tree-based indexing
  • 2-3 trees
  • B-trees
  • B+ trees
  • B-tree analysis
  • Exercises
  • Summary
  • Chapter 8: Graphs
  • Terminology and representations
  • Graph implementations
  • Graph traversals
  • Depth-first search
  • Breadth-first search
  • Topological sort
  • Shortest path problems
  • Single-source shortest paths
  • Minimum-cost spanning tree
  • Prim's algorithm
  • Kruskal's algorithm
  • Exercises
  • Summary
  • Chapter 9: Programming and Randomized Algorithms
  • Dynamic programming
  • The knapsack problem
  • All pairs shortest paths
  • Randomized algorithms
  • Randomized algorithms for finding large values
  • Skip lists
  • Probabilistic analysis of skip lists
  • Exercises
  • Summary
  • Chapter 10: Functional Data Structures
  • Functional data structure
  • Lazy evaluation
  • Functional stacks
  • Functional queues
  • Fast fully-persistent queues
  • Slowly-persistent queues and deques
  • Summary
  • Index.

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