About this ebook
In this chapter, foundations of robust statistics are introduced, including classic and robust estimators as well as their statistical properties (breakdown point, efficiency, influence function and equivariance property). Then, some robust methods that have gained popularity in recent years are presented. The major benefit of using robust methods stems from the fact that they help providing stable estimates for data containing outliers (food samples that have considerably different compositions in comparison with the majority of samples). Regardless of reasons for their uniqueness, outliers strongly affect data interpretation when any method with the least-squares cost function is used. Therefore, robust methods are more suitable to explore and model data containing natural samples when outliers are expected. In addition to exploration and modeling of multivariate data, processing of incomplete multivariate data that contain outliers is also discussed.
Rate this ebook
Tell us what you think.
Reading information
Smartphones and tablets
Install the Google Play Books app for Android and iPad/iPhone. It syncs automatically with your account and allows you to read online or offline wherever you are.
Laptops and computers
You can listen to audiobooks purchased on Google Play using your computer's web browser.
eReaders and other devices
To read on e-ink devices like Kobo eReaders, you'll need to download a file and transfer it to your device. Follow the detailed Help Center instructions to transfer the files to supported eReaders.
