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

Dynamic programming


Dynamic programming can be defined as an approach that uses a recurrent formula (breaking a problem into a subproblem) to solve any complex problem. A sub-solution of any problem is reconstructed using the previous state solution. Dynamic programming-based approaches are able to achieve a polynomial complexity for solving problems, and assure faster computation than other classical approaches, such as brute force algorithms. Before we get into dynamic programming, let's cover the basics of DAG, as it will help with implementation of dynamic programming. DAGs are directed acyclic topological graphs, which are defined by a number of vertices and edges such that every edge is directed from earlier to later in the sequence. An example of a DAG is shown in Figure 9.1:

Figure 9.1: An example of DAG

Let's assume that the vertices represent cities and edges represent the path to be followed to reach a particular city. The objective is to determine the shortest path to node D...