Times Series Analysis Without Model Identification.

  title={Times Series Analysis Without Model Identification.},
  author={Wayne F. Velicer and R. P. Mcdonald},
  journal={Multivariate behavioral research},
  volume={19 1},
Time series analysis is a method for analyzing repeated observations on a single unit. Previously developed approaches involve a two stage process: (1) identifying which of various ARIMA (p,d,q) models best describe the underlying process; and (2) on the basis of the identified model, transforming the observed data to meet the assumptions (i.e., independence of data) of the general linear model, and estimating and testing the intervention effects. The present paper explores employing a general… CONTINUE READING

From This Paper

Topics from this paper.

Similar Papers

Loading similar papers…