Structure Identification in the Intrinsic Case

This page constitutes an add-on to the User’s Guide for Statistics / Exploratory Data Analysis.

This technical reference reviews the main tools available in Isatis to describe the spatial variability (regularity, continuity, ...) of the variable(s) of interest, commonly referred to as the "Structure", in the Intrinsic Case.

References

1. Akaike, Hirotugu (1974). "A new look at the statistical model identification». IEEE Transactions on Automatic Control 19 (6): 716‑723. doi:10.1109/TAC.1974.1100705. MR0423716.
2. Brockwell, P.J., and Davis, R.A. (2009). Time Series: Theory and Methods, 2nd ed. Springer.
3. Burnham, K. P., and Anderson, D.R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd ed. Springer-Verlag. ISBN 0-387-95364-7.
4. Burnham, K. P., and Anderson, D.R. (2004), "Multimodel inference: understanding AIC and BIC in Model Selection", Sociological Methods and Research, 33: 261-304.
5. Cavanaugh, J.E. (1997). "Unifying the derivations of the Akaike and corrected Akaike information criteria", Statistics and Probability Letters, 31:201-208.
6. Hurvich, C. M., and Tsai, C.-L. (1989). "Regression and time series model selection in small samples", Biometrika, 76: 297‑307.
7. Schwarz, Gideon. 1978. Estimating the Dimension of a Model. Annals of Statistics 6:461-4.6