Time series model identification by estimating information, memory and quantiles.

Emanuel Parzen

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A scratch removal method

Michal Haindl, Stanislava Šimberová (1998)

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We present a new type of scratch removal algorithm based on a causal adaptive multidimensional prediction. The predictor use available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data but not any information from failed pixel itself. Predictor parameters cannot be directly identified so a special approximation is introduced.

Instability and long memory in conditional variances

Ignacio Mauleón (1997)

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M'hammed Baba Harra (1997)

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Given a realization on a finite interval of a continuous-time stationary process, we construct estimators for higher order spectral densities. Tapering and shift-in-time methods are used to build estimators which are asymptotically unbiased and consistent for all admissible values of the argument. Asymptotic results for the fourth-order densities are given. Detailed attention is paid to the nth order case.

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The empirical TES methodology: Modeling empirical time series.

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Imre Bártfai (2002)

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