• Corpus ID: 233423350

Changepoint detection in random coefficient autoregressive models

@inproceedings{Horvth2021ChangepointDI,
  title={Changepoint detection in random coefficient autoregressive models},
  author={Lajos Horv{\'a}th and Lorenzo Trapani},
  year={2021}
}
Abstract. We propose a family of CUSUM-based statistics to detect the presence of changepoints in the deterministic part of the autoregressive parameter in a Random Coefficient AutoRegressive (RCA) sequence. In order to ensure the ability to detect breaks at sample endpoints, we thoroughly study weighted CUSUM statistics, analysing the asymptotics for virtually all possible weighing schemes, including the standardised CUSUM process (for which we derive a Darling-Erdős theorem) and even heavier… 
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