Abstract
In this paper, we consider the problem of weakly consistent offline clustering of ARMA processes. Under the provided assumptions we derive a weakly consistent clustering algorithm of invertible ARMA processes according to their forecast functions. Using BIC penalized quasi-maximum likelihood estimate of the distance function the weak consistency of Algorithm 1 is proven when the target number of clusters is known. The theoretical lower bound of the clustering function is provided.
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Adamyan, G.L. Weakly Consistent Offline Clustering of ARMA Processes. J. Contemp. Mathemat. Anal. 58, 183–190 (2023). https://doi.org/10.3103/S1068362323030020
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DOI: https://doi.org/10.3103/S1068362323030020