{
  "annotation_id": "d331c904-8682-499b-beab-a9146978ccbf",
  "date_created": "2026-03-02T18:00:49.727000Z",
  "date_modified": "2026-03-02T18:00:49.727000Z",
  "file_hash": "c44e672cccda02492fb538e3af0ee9a86fe553b7e80d7df95e6f277feec64e49",
  "private": false,
  "record": {
    "abstract": "Stress time series from the PLC effect typically exhibit stick-slips of\nupload and download type. These data contain strong short-term correlations of\na nonlinear type. We investigate whether there are also long term correlations,\ni.e. the successive up-down patterns are generated by a deterministic\nmechanism. A statistical test is conducted for the null hypothesis that the\nsequence of the up-down patterns is totally random. The test is constructed by\nmeans of surrogate data, suitably generated to represent the null hypothesis.\nLinear and nonlinear estimates are used as test statistics, namely\nautocorrelation, mutual information and Lyapunov exponents, which are found to\nhave proper performance for the test. The test is then applied to three stress\ntime series under different experimental conditions. Rejections are obtained\nfor one of them and not with all statistics. From the overall results we cannot\nconclude that the underlying mechanism to the PLC effect has long memory.",
    "arxiv_id": "physics/0405097",
    "authors": [
      "Dimitris Kugiumtzis",
      "Elias C. Aifantis"
    ],
    "categories": [
      "physics.data-an"
    ],
    "title": "Statistical Analysis for Long Term Correlations in the Stress Time   Series of Jerky Flow",
    "url": "https://arxiv.org/abs/physics/0405097"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "c07090b2-e032-40fb-9c1d-8c64fe517726",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}