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.
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