Experimental assessment of traffic density estimation at link and network level with sparse data

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A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...

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Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

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Activity-based models offer the potential of a far deeper understanding of daily mobility behaviour than trip-based models. However, activity-based models used both in research and practice have often relied on applying sequential choice models between sub ...

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Experimental assessment of traffic density estimation at link and network level with sparse data

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Density estimation in RKHS with application to Korobov spaces in high dimensions

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Timing and spatial selection bias in rapid extreme event attribution

Sparsely Observed Functional Time Series: Theory and Applications

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