Least Squares: Optimization Techniques for Computer Vision: Least Squares Methods
About this ebook
The method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals made in the results of each individual equation.
How you will benefit
(I) Insights, and validations about the following topics:
Chapter 1: Least squares
Chapter 2: Gauss-Markov theorem
Chapter 3: Regression analysis
Chapter 4: Ridge regression
Chapter 5: Total least squares
Chapter 6: Ordinary least squares
Chapter 7: Weighted least squares
Chapter 8: Simple linear regression
Chapter 9: Generalized least squares
Chapter 10: Linear least squares
(II) Answering the public top questions about least squares.
(III) Real world examples for the usage of least squares in many fields.
Who this book is for
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Least Squares.
