Methods for logistic growth curve parameters estimation. Part. 1. Optimization of estimation conditions at the presence of additive random error

Logistic growth is one of the traditional mathematical models, used for describing many population processes in particular, the dynamics of DNA quantity in polymerase chain reaction in real time (PCR-RT) is adequately described by a similar model. The parameters of the logistic growth curve serve the basis for the development of the necessary analytical information about the initial quantity of genetic material. The subject of the study is the sequence of measurements, each of which, in a general case, besides useful informative component contains random centered additive error and systematic component as a linear trend of the first order with a priori unknown parameters. The aim of the present part of the study is the development of the algorithms of the effective parameters estimation of logistic growth in the presence of the additive centered limited random error.