Annotation

Annotation: An algorithm for constructing a regression equation for processing the results of bird monitoring in the study area in the form of a multidimensional polynomial by the least squares method is proposed. An interactive program Birds_MLS is developed in the Python algorithmic language, which provides the calculation of the equation coefficients using the NumPy, Pandas, SciPy, Matplotlib, and PyQt6 libraries. The program contains a full cycle of calculations, starting with the introduction of initial data, building a regression model, and ending with checking its validity and visualizing the results. The validity of the proposed model is assessed using the R^2 determination index and the F-Fisher criterion. The adequacy criteria are determined by comparing the known dependence of the u(x,y) function on two coordinates with the results of calculations obtained using the v(x,y) regression equation. The testing experiments confirmed the adequacy of the proposed algorithm when studying the dependence of population size on multiple variables in a multivariate setting.