This article examines the previously studied linear in factors and non-linear in parameters modular regression model containing unary module operations. Through the use of binary, ternary, ..., l-ary module operations, a generalization of modular regression was proposed for the first time. A special case of generalization is considered - regression with a multiary operation modulus. The problem of accurately estimating such a model using least absolute deviations is reduced to a mixed integer 0-1 linear programming problem. Using data on farm productivity built into the Gretl econometric package, classical linear regression and modular regression with a multivariate operation were built. The quality of approximation of the proposed modular regression turned out to be higher than the quality of the linear model.

Keywords: regression analysis, modular regression, least absolute deviations, multiary operation modulus, mixed integer 0-1 linear programming problem