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• W2093753881 abstract "[1] Utsu, Aki, and others have formulated earthquake probabilities on the basis of precursory anomalies in multidisciplinary observations, assuming that occurrences of one kind of precursory anomaly are independent from those of another. We extend their studies to cases where precursory anomalies depend on one another. We consider two kinds of distributions for each precursory parameter, those associated with only space-time volumes in the vicinity of target events (conditional density distributions) and those associated with space-time volumes not including target events within a short distance (background density distributions). Treating precursory anomalies as continuous variables, we assume that the conditional and background densities from each discipline are normally distributed. We obtain analytical solutions for the general case in which mutual correlations exist among precursory anomalies in both distributions. First, we consider the case in which observations are correlated with one another in the conditional density distribution but not in the background density distribution, and then the case in which observations are correlated in both distributions. The result obtained in the first case is compared with cases in which the observations are independent of one another in both distributions. This comparison leads to the conclusion that the mean probability gain is always larger in the correlated case than in the independent case. The ratio of the former to the latter is expressed in terms of correlation coefficients and becomes infinitely large when the absolute value of the correlation coefficient approaches 1. Analytical solutions for the two-dimensional case are given in an explicit form. Applying these solutions to distributions of the Gutenberg-Richter a and b values observed in Kanto, Japan, we obtained a combined model with a and b values that outperform either model of the Gutenberg-Richter relation, with a universal b value or a variable one. These findings could be applied in combining a wide range of multidisciplinary observations into a single model of earthquake probability." @default.
• W2093753881 created "2016-06-24" @default.
• W2093753881 creator A5071671678 @default.
• W2093753881 date "2007-05-17" @default.
• W2093753881 modified "2023-09-27" @default.
• W2093753881 title "Information gain of a model based on multidisciplinary observations with correlations" @default.
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• W2093753881 doi "https://doi.org/10.1029/2006jb004662" @default.
• W2093753881 hasPublicationYear "2007" @default.
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