In this section, we will introduce the preliminary of

matrix calculus theory and derive the general form of the second-order sensitivity formula for equilibrium network flows.

Mathematical expertise required is Limited to differential and

matrix calculus. The various stages necessary for the implementation of the method are clearly identified, with a chapter given over to each one: approximation, construction of the integral forms, matrix organization, and solution of the algebraic systems and architecture of programs.

Using these properties and noting that also [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], the following can be seen by exploiting simple

matrix calculus.

A solid background in linear regression (particularly multivariable linear regression) is assumed and experience with basic differential calculus, integral calculus, probability theory, and

matrix calculus will aid in understanding the material.

He cover principal component analysis, multiple correspondence analysis, the factorial analysis of mixed data, weighting groups of variables, comparing clouds of partial individuals, factors common to different groups of variables, comparing groups of variables and the Indscal model, qualitative and mixed data, multiple factor analysis and Procrustes analysis, hierarchical multiple factor analysis, and

matrix calculus and Euclidean vector space.