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The modelling approach exploits the author's Data-Based Mechanistic (DBM) modelling philosophy, combined with powerful methods of recursive statistical estimation.
Recruitment and baseline data will be used to develop statistical models that relate the independent variables to the dependents: Multimorbidity patterns of similar severity will be identified by methods of supervised learning (methods of recursive partitioning like CART [Classification and Regression Trees], logistic regression).
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In this paper, a novel direct method of recursive identification of the Preisach hysteresis density function is proposed.
This paper addresses a new design method of recursive least-squares (RLS) and finite impulse response (FIR) filter, using covariance information, in linear continuous-time stochastic systems.
This paper addresses a new design method of recursive least-squares (RLS) finite impulse response (FIR) filter, using the covariance information of the signal and observation noise, and RLS Wiener FIR filter in linear discrete-time stochastic systems.
Focused on the non-stationarity and real-time analysis of signal in flutter test with progression variable speed (FTPVS), a new method of recursive time-frequency analysis is presented.
Our method of recursive feature addition (RFA) employs supervised learning to achieve the best training accuracy and uses statistical similarity measures to choose the next variable with the least dependence on, or correlation to, the already identified variables as follows: Insignificant genes are removed according to their statistical insignificance.
An overview of methods for recursive parameter estimation in adaptive filtering is given in the literature [5 7].
Other, less interpretable methods include various types of recursive partitioning, such as random forests, support vector machines, and neural networks [ 29- 32].
This paper presents a simple and efficient method for the design of recursive digital fractional order integrator when the order of integration is a real number between 0 and 1.
A third group of methods revisits recursive P-value computation, with a O(S× N) time complexity.
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