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- W2244737014 abstract "We propose a latent-class model where the joint distribution of linear and circular data is specified through a finite mixture of conditionally independent Gamma and von Mises distributions. Missing values are imputed by drawing multiple imputations from the predictive distribution of the missing values given the observed data, at the maximum likelihood estimates. The procedure is illustrated on an incomplete dataset that includes measurements of wind speed and direction and significant wave height and direction, taken by a buoy and two tide gauges of the Italian wave-metric network." @default.
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- W2244737014 date "2010-01-01" @default.
- W2244737014 modified "2023-09-27" @default.
- W2244737014 title "A latent-class approach to missing value imputation in incomplete multivariate wave metric datasets" @default.
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