Linear transformations - Matrix transformations - Linear Algebra - Khan Academy
Matrix Differential Calculus with Applications in Statistics and Econometrics pdf
In statistics , a design matrix , also known as model matrix or regressor matrix and often denoted by X , is a matrix of values of explanatory variables of a set of objects. Each row represents an individual object, with the successive columns corresponding to the variables and their specific values for that object. The design matrix is used in certain statistical models , e. The design matrix contains data on the independent variables also called explanatory variables in statistical models which attempt to explain observed data on a response variable often called a dependent variable in terms of the explanatory variables. The theory relating to such models makes substantial use of matrix manipulations involving the design matrix: see for example linear regression. A notable feature of the concept of a design matrix is that it is able to represent a number of different experimental designs and statistical models, e. A regression model which is a linear combination of the explanatory variables may therefore be represented via matrix multiplication as.
Search in Amazon. This exhaustive, self-contained book on matrix theory and matrix differential calculus provides a treatment of matrix calculus based on differentials and shows how easy it is to use this theory once you have mastered the technique. Jan Magnus, who, along with the late Heinz Neudecker, pioneered the theory, develops it further in this new edition and provides many examples along the way to support it.
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