About the least-squares method, adapted to the Pearson-Jeffreys law of errors
Introduction. K.F. Gausse creates the classical least-square method (LSM) based on the hypothesis of normality of the observation errors. However this hypothesis, as a rule, is uncapable, if the number of the numerous instrumentation is n>500. In this case the errors are described with the Pearson-Jeffreys symmetrical threeparametrical distribution, which as the Gausse law has the diagonal information matrix and one can name it as the universal distribution law of overall size errors in accordance with numerous research.