COEFFICIENTS OF REGRESSION, CONTAINING MATHEMATICALLY INTRODUCED AND COGNITIVELY EXTRACTABLED KNOWLEDGE.
The article developed a variant of the Inverse Model of Multiple Linear Regression Analysis (OM MLRA with given regression coefficients (?1,…,?n-1)T,Z+2Z+1?, Z+mn[Z+1?Z+2], containing mathematically int of produced and cognitively extracted knowledge With the use of equalities from Inverse Model the Principal Component Analysis (IM PCA) solved a New Inverse Generalized Problem of Multiple Linear Regression Analysis (IGM MLRA) of statistical modeling of n-1 correlated z-variables, 1 z-variable: Z+mn[Z+1?Z+2],Z+2Z+1?, satisfying all equations and relations in DM MLRA: (Z+1,Z+2)(R-111,R12,?). Simulated (?,C+11)--samples Z+mn[Z+1?Z+2], Z+2Z+1?, in the presence of a partition, and the extraction of knowledge - without partitioning the set of z - variables. The input parameters of the IGP of MLRA are the vector ?(?1,…,?n-1)T and the matrix of eigenvectors C+11. The numerical algorithms were tested using the example of modeling a multidimensional (?,C+11)-sample of z -variables (with n6). The designated vector ?(?1…,?6)T regression coefficients was used. A description of the reverse process of extracting the knowledge entered using cognitive modeling will be published in another article.