Francisco, Gerson [UNESP]Muruganandam, Paulsamy [UNESP]2014-05-272014-05-272003-06-01Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, v. 67, n. 6 2, 2003.1063-651Xhttp://hdl.handle.net/11449/67300Predictability is related to the uncertainty in the outcome of future events during the evolution of the state of a system. The cluster weighted modeling (CWM) is interpreted as a tool to detect such an uncertainty and used it in spatially distributed systems. As such, the simple prediction algorithm in conjunction with the CWM forms a powerful set of methods to relate predictability and dimension.engAlgorithmsBoundary conditionsEigenvalues and eigenfunctionsForecastingMatrix algebraProbabilityProbability distributionsRandom processesStatistical methodsVectorsBayesian modelingDynamical systems theoryFinite time predictionLocal dimensionSpatiotemporal chaotic systemChaos theoryArtigo10.1103/PhysRevE.67.066204WOS:000184085000038Acesso aberto2-s2.0-427491080432-s2.0-42749108043.pdf