Nov 5, 2023 · This paper proposes a new approach to fuzzy clustering of time series based on the dissimilarity among conditional higher moments.

This paper proposes a new approach to fuzzy clustering of time series based on the dissimilarity among conditional higher moments. A system of weights ...

Jan 1, 2024 · Abstract. This paper proposes a new approach to fuzzy clustering of time series based on the dissimilarity among conditional higher moments.

Jul 15, 2022 · This paper aims to develop a novel approach that faces still open issues in moment-based clustering.

Title. Fuzzy clustering of time series based on weighted conditional higher moments. Authors. Cerqueti, Roy; D'Urso, Pierpaolo; De Giovanni, Livia; Mattera, ...

The usefulness of the proposed fuzzy clustering of time series based on the dissimilarity among conditional higher moments is provided with simulated data ...

In this paper, assuming that the time series follows a multifractional Brownian motion, we estimate a time-varying Hurst exponent used as the input for a fuzzy ...

Oct 22, 2024 · This paper develops a new time series clustering procedure allowing for heteroskedasticity, non-normality and model's non-linearity.

This paper develops a new time series clustering procedure allowing for heteroskedasticity, non-normality and model's non-linearity. At this aim, we follow a ...

The algorithm for both the conditional and unconditional moments-based clustering are reported in the Algorithm 1 and Algorithm 2 tables. Two crucial aspects of ...