Construction of a piece-linear autoregression model of an arbitrary order

Abstract

The relevance of the study is due to the need to expand the arsenal of forms of communication between variables in regression models. Object: piecewise linear autoregressive model of arbitrary order. Subject: computing apparatus for solving problems of linear-Boolean programming. Purpose: development of an algorithm for estimating the parameters of piecewise linear regression. Methods: regression analysis, mathematical programming. Results: the paper formulated the problem of constructing a piecewise linear autoregressive model of an arbitrary order based on the method of least modules. An algorithm for solving it is proposed, which reduces to a linear Boolean programming problem of acceptable dimension for real applied problems. A piecewise linear autoregressive model of housing provision based on the statistical information of the Irkutsk region has been developed, which has a high adequacy. The model can be successfully used in solving various predictive problems. Keywords: regression model, autoregression, least modules method, linear Boolean programming problem, housing supply.