1. A method to process measurement data comprised of a plurality of data sets with a plurality of independent random samples originating via temporally successive measurements comprising the steps of: for each independent random sample in the data set, comparing a measured time curve arising from measurement data x of the random sample, using the general linear model, with a time curve of at least one model function of a model matrix G, to test for incidence of specific characteristics in the measured time curve; implementing individual calculations for the comparison from the measurement data in a sequence of the of the data sets, or volume data sets originating from the time sequence of the measurements, for all relevant measurement data of a volume data set and storing said calculations as intermediate results; updating the intermediate results from a directly preceding volume data set with new calculations, such that at any time intermediate results can be calculated, and after a one-time cycle of all volume data sets an end result exists from which an assertion about the incidence of the characteristics in the signal curve is derived; and obtaining the square of an error vector for the intermediate or end result from a difference of the square of a measurement value vector formed from the measurement data and the square of a model vector calculated from the model function.