Book Image

Simulation for Data Science with R

By : Matthias Templ
Book Image

Simulation for Data Science with R

By: Matthias Templ

Overview of this book

Data Science with R aims to teach you how to begin performing data science tasks by taking advantage of Rs powerful ecosystem of packages. R being the most widely used programming language when used with data science can be a powerful combination to solve complexities involved with varied data sets in the real world. The book will provide a computational and methodological framework for statistical simulation to the users. Through this book, you will get in grips with the software environment R. After getting to know the background of popular methods in the area of computational statistics, you will see some applications in R to better understand the methods as well as gaining experience of working with real-world data and real-world problems. This book helps uncover the large-scale patterns in complex systems where interdependencies and variation are critical. An effective simulation is driven by data generating processes that accurately reflect real physical populations. You will learn how to plan and structure a simulation project to aid in the decision-making process as well as the presentation of results. By the end of this book, you reader will get in touch with the software environment R. After getting background on popular methods in the area, you will see applications in R to better understand the methods as well as to gain experience when working on real-world data and real-world problems.
Table of Contents (18 chapters)
Simulation for Data Science with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
Index

Properties of estimators


Especially in the following chapters, designations such as bias or asymptotic unbiasedness will be used repeatedly. These expressions are used to describe properties of an estimator. These terms are explained briefly here.

Assumption: The distribution of the sample elements has an unknown parameter . A function t that approximately estimates from the sample values the parameter is given by:

Generally a function of a sample, is noted as statistics. In the case of estimation of parameters, we talk about a function for estimation, short estimator t. The realization of an estimator, such as is called estimation.

Depending on the sample obtained, other results for the point estimate are gained. For example, if 1,000 people are asked about their income by drawing 1,000 people from a finite population, the mean income would differ when another 1,000 people are drawn. Practically speaking, performed point estimates are therefore only useful when the accuracy of the results...