Simulation for Data Science with R
This book gets you up to speed with the important and fundamental concepts in statistical modeling and simulation. Using real-world case studies, you’ll be able to learn effectively and apply your skills later in the real world.
Offered by
Difficulty Level
Intermediate
Completion Time
13h16m
Language
English
About Book
Who Is This Book For?
This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required.
Simulation for Data Science with R
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 13h16m total length
Introduction
R and high-performance computing
The discrepancy between Pencil driven theory and Data driven computational solutions
Simulation of random numbers
Monte-Carlo methods for optimization problems
Probability theory shown by simulation
Resampling Methods
Applications of resampling methods and Monte Carlo tests
The EM algorithm
Simulation of complex data
System dynamics
Related Resources
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