Publications by Tomas Masák | EPFL Graph Search

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This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the covariance, even ...

Nonparametric inference for functional data over two-dimensional domains entails additional computational and statistical challenges, compared to the one-dimensional case. Separability of the covariance is commonly assumed to address these issues in the de ...

The nonparametric estimation of covariance lies at the heart of functional data analysis, whether for curve or surface-valued data. The case of a two-dimensional domain poses both statistical and computational challenges, which are typically alleviated by ...

Tomas Masák

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Covariance Estimation for Random Surfaces beyond Separability

Random Surface Covariance Estimation by Shifted Partial Tracing

Inference and Computation for Sparsely Sampled Random Surfaces

Separable expansions for covariance estimation via the partial inner product