Optimal Experimental Design with R

✍ Scribed by Dieter Rasch, Jurgen Pilz, L.R. Verdooren, Albrecht Gebhardt

Publisher: Chapman and Hall/CRC
Year: 2011
Tongue: English
Leaves: 341
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question.

Providing a concise introduction to experimental design theory, Optimal Experimental Design with R:

Introduces the philosophy of experimental design
Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs
Teaches by example using a custom made R program package: OPDOE

Consisting of detailed, data-rich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis testing, and confidence estimation. A final chapter of in-depth theoretical details is included for interested mathematical statisticians.

📜 SIMILAR VOLUMES

Optimal Experimental Design with R

📁 Optimal Experimental Design with R

✍ Dieter Rasch, Jurgen Pilz, L.R. Verdooren, Albrecht Gebhardt 📂 Library 📅 2011 🏛 Chapman and Hall/CRC 🌐 English

Experimental Design and Process Optimiza

📁 Experimental Design and Process Optimization

✍ Maria Isabel Rodrigues, Antonio Francisco Iemma 📂 Library 📅 2014 🏛 CRC Press 🌐 English

Experimental Design and Process Optimization delves deep into the design of experiments (DOE). The book includes Central Composite Rotational Design (CCRD), fractional factorial, and Plackett and Burman designs as a means to solve challenges in research and development as well as

Experimental Design and Process Optimiza

📁 Experimental Design and Process Optimization

✍ Maria Isabel Rodrigues; Antonio Francisco Iemma 📂 Library 📅 2014 🏛 CRC, Taylor and Francis 🌐 English

Functional Approach to Optimal Experimen

📁 Functional Approach to Optimal Experimental Design

✍ Viatcheslav B. Melas (auth.) 📂 Library 📅 2006 🏛 Springer-Verlag New York 🌐 English

The book presents a novel approach for studying optimal experimental designs. The functional approach consists of representing support points of the designs by Taylor series. It is thoroughly explained for many linear and nonlinear regression models popular in practice including polynomial, tr

Optimum Experimental Designs, with SAS

📁 Optimum Experimental Designs, with SAS

✍ Anthony Atkinson, Alexander Donev, Randall Tobias 📂 Library 📅 2007 🏛 Oxford University Press, USA 🌐 English

Modern Optimization with R

📁 Modern Optimization with R

✍ Paulo Cortez 📂 Library 📅 2021 🏛 Springer Nature Switzerland AG 🌐 English

The goal of this book is to gather in a single work the most relevant concepts related in optimization methods, showing how such theories and methods can be addressed using the open source, multi-platform R tool. Modern optimization methods, also known as metaheuristics, are particularly useful for