Relative information: theories and applications
Relative information: theories and applications
Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
Elements of information theory
Elements of information theory
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Primal-dual interior-point methods
Primal-dual interior-point methods
High-Order Pattern Discovery from Discrete-Valued Data
IEEE Transactions on Knowledge and Data Engineering
A Mathematical Theory of Communication
A Mathematical Theory of Communication
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An information-statistical approach is proposed for analyzing temporal-spatial data. The basic idea is to analyze the temporal aspect of the data by first conditioning on specific spatial nature of the data. Parametric approach based on Guassian model is employed for analyzing the temporal behavior of the data. Schwarz information criterion is then applied to detect multiple mean change points -- thus the Gaussian statistical models -- to account for changes of the population mean over time. To examine the spatial characteristics of the data, successive mean change points are qualified by finite categorical values. The distribution of the finite categorical values is then used to estimate a non-parametric probability model through a non-linear SVD-based optimization approach; where the optimization criterion is Shannon expected entropy. This optimal probability model accounts for the spatial characteristics of the data and is then used to derive spatial association patterns subject to chisquare statistic hypothesis test.