Book Image

R Data Structures and Algorithms

By : PKS Prakash, Achyutuni Sri Krishna Rao
Book Image

R Data Structures and Algorithms

By: PKS Prakash, Achyutuni Sri Krishna Rao

Overview of this book

In this book, we cover not only classical data structures, but also functional data structures. We begin by answering the fundamental question: why data structures? We then move on to cover the relationship between data structures and algorithms, followed by an analysis and evaluation of algorithms. We introduce the fundamentals of data structures, such as lists, stacks, queues, and dictionaries, using real-world examples. We also cover topics such as indexing, sorting, and searching in depth. Later on, you will be exposed to advanced topics such as graph data structures, dynamic programming, and randomized algorithms. You will come to appreciate the intricacies of high performance and scalable programming using R. We also cover special R data structures such as vectors, data frames, and atomic vectors. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. We will also explore the application of binary search and will go in depth into sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort.
Table of Contents (17 chapters)
R Data Structures and Algorithms
Credits
About the Authors
Acknowledgments
About the Reviewer
www.PacktPub.com
Preface

Chapter 9. Programming and Randomized Algorithms

In the preceding chapters, we covered some fundamental data structures and algorithms. The current chapter extends static algorithm (deterministic algorithm) concepts to randomized algorithms. Deterministic algorithms use polynomials of the size of the input, whereas random algorithms use random sources as input and make their own choices. The chapter will introduce the Las Vegas and the Monte Carlo randomized algorithms and their application using examples. The chapter will also introduce skip list and its extended version, randomized skip list, which uses randomization concepts to reduce the computation effort in an average case scenario. We will start with the fundamentals of programming, which can be used to reduce computational effort in intensive tasks. The current chapter will cover the concepts of dynamic programming and directed acyclic graphs (DAGs). The current chapter will cover following topics:

  • Dynamic programming

    • The knapsack...