Optimal design of sea-walls requires the extreme value analysis of a variety of oceanographic data. Asymptotic arguments suggest the use of multivariate extreme value models, but empirical studies ...
Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...
A new form of non-linear autoregressive time series is proposed to model solar radiation data, by specifying joint marginal distributions at low lags to be multivariate Gaussian mixtures. The model is ...
We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...
Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.
TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...
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