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Multivariate autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry
Multivariate autoregressive modelling sea level time series TOPEX/Poseidon satellite altimetry
2009/11/9
This work addresses the autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry mission. Datasets from remote sensing applications are typically very large and correl...
Multivariate non-normally distributed random variables in climate research–introduction to the copula approach
random variables climate research introduction copula approach
2009/11/2
Probability distributions of multivariate random variables are generally more complex compared to their univariate counterparts which is due to a possible nonlinear dependence between the random varia...
Denoising gravity and geomagnetic signals from Etna volcano (Italy) using multivariate methods
geomagnetic signals Etna volcano multivariate methods
2009/11/2
Multivariate methods were applied to denoise the gravity and geomagnetic signals continuously recorded by the permanent monitoring networks on the Etna volcano. Gravity and geomagnetic signals observe...
Multivariate analysis of nonlinearity in sandbar behavior
Multivariate analysis nonlinearity sandbar behavior
2009/10/30
Alongshore sandbars are often present in the nearshore zones of storm-dominated micro- to mesotidal coasts. Sandbar migration is the result of a large number of small-scale physical processes that are...
Information theoretic measures of dependence,compactness,and non-gaussianity for multivariate probability distributions
Information theoretic measures non-gaussianity multivariate probability distributions
2009/10/30
A basic task of exploratory data analysis is the characterisation of "structure" in multivariate datasets. For bivariate Gaussian distributions, natural measures of dependence (the predictive relation...