Регрессионный анализ в прогнозировании пририродно-очаговых инфекций

Abstract

Regression analysis - a set of statistical methods for processing of experimental data to a condition
 of stochastic dependence study of the value of non-random or random variables to define this relationship.
 Statement of the problem of regression analysis is formulated as follows. There is a set of observational results.
 Requires a quantitative relationship between the index and factors.
 In this paper, we try to establish a quantitative relationship between the incidence of natural - focal infections
 and biotic and abiotic factors of the environment. By biotic factors include: the number of infection and the
 major carriers and vectors to abiotic factors - weather (average monthly air temperature, the monthly average
 rainfall, snow depth in December, January, February, March).
 When studying the effect of 22 factors on the incidence of leptospirosis using multiple regression the mathematical
 model, which has a low level of trust, and when using the stepwise regression established the influence
 of one factor - infection of the common vole of the 22 factors. Level of trust models and model coefficients
 are significant. This method allows to determine only the linear relationship between the incidence and natural
 factors, as in the case of the nonlinear coupling tightness does not install.
 Natural foci of infection is a complex ecological system. Based on the terms of modeling complex systems,
 which may include: the possible impact of non-linear elements in the output parameter, synergy and reciprocity
 under the joint influence of individual factors, the need to address in some cases categorical factors and
 multiple output parameters of a complex system, it is necessary to choose an artificial neural network (ANN),
 allowing to realize these conditions in the preparation of a mathematical model of the system.