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In chapter 1 the basic problem of the confluent, confluent-variance and confluent-regression analysis of passive experiment: a problem of estimation of unknown parameters is solved algebraically. The problem of the robust estimation of normal parameters of incomplete-rank confluent and confluent-regression model is solved also.

In the second chapter, the models of the passive-active-regression experiment are constructed. A picture of exposition of experimental researches in frameworks of the confluent-influent-regression models is finished. That allows the contributor to understand better to itself a picture of researches and to carry out correctly parameters' estimation. The method of the effective correction of rounding errors is constructed also for the procedure of the numerical solution of the SLAE and of the numerical computation of parameters' estimates. The regularized estimation methods for a case of the incomplete-rank matrices are developed.

In this chapter we allow for deterministic and random errors in variational methods that construct the pseudosolution of linear integral equations of the second kind and the regularized pseudosolution and quasisolution of the linear integral equations of the first kind. We consider both passive errors (i.e., errors during observation or measurement) in the right-hand side and passive or active errors (i.e., errors during specification) in the core. We consider the representation methods of the a priori information on a sought pseudosolution using the mixed models and the statistical regularization methods. We construct the numerical realization of these methods.