Computerized method and apparatus for iterative calculation of the general linear model using only substantially orthogonal model functions

Abstract

In a method and apparatus for incremental calculation of a general linear model given intermittent correlation of the model functions, data composed of a number of data sets with a number of different random samples are processed. For each independent random sample contained in the data set, a dependency on an order quantity is compared with the dependency on the order quantity in model functions contained in a model matrix G using the general linear model in order to check the occurrence of specific characteristics in the dependency of the random sample on the order quantity. The calculation of the general linear model ensues incrementally from data set to data set. Before the calculations for the data of a data set, a check is made as to whether the model functions contained in the model matrix G exhibit orthogonal portions to a sufficient degree in a segment (represented by the data set) of the dependency on the order quantity for the calculations. Given a degree of parallelism that is too high, one or more model functions of the model matrix G that interfere with the orthogonality are masked out to a predeterminable degree in the calculations for this data set, in order to achieve the sufficient degree of orthogonal portions. An incremental calculation of the general linear model with corresponding output of intermediate results is thereby enabled, even given the presence of intermittent correlating model functions in the model matrix.