{
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  "Package": "SNSeg",
  "Title": "Self-Normalization(SN) Based Change-Point Estimation for Time\nSeries",
  "Version": "1.0.3",
  "Authors@R": "c(person(\"Shubo\",\"Sun\",role=c(\"aut\"),email = \"sxs3935@miami.edu\"),\nperson(\"Zifeng\",\"Zhao\",role = c(\"aut\",\"cre\"),email = \"zzhao2@nd.edu\"),\nperson(given = \"Feiyu\",family = \"Jiang\",role = c(\"aut\"),email = \"jiangfy@fudan.edu.cn\"),\nperson(\"Xiaofeng\",family = \"Shao\",role = c(\"aut\"),email = \"xshao@illinois.edu\")\n)",
  "Description": "Implementations self-normalization (SN) based algorithms\nfor change-points estimation in time series data. This\ncomprises nested local-window algorithms for detecting changes\nin both univariate and multivariate time series developed in\nZhao, Jiang and Shao (2022) <doi:10.1111/rssb.12552>.",
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  "Author": "Shubo Sun [aut], Zifeng Zhao [aut, cre], Feiyu Jiang [aut],\nXiaofeng Shao [aut]",
  "Maintainer": "Zifeng Zhao <zzhao2@nd.edu>",
  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2024-06-03 02:41:53 UTC",
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    "SNSeg_Multi",
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    {
      "page": "critical_values_HD",
      "title": "Critical Values of Self-Normalization (SN) based test statistic for changes in high-dimensional means (SNHD)",
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    {
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    {
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      "page": "MAR",
      "title": "A funtion to generate a multivariate autoregressive process (MAR) in time series",
      "topics": [
        "MAR"
      ]
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    {
      "page": "MAR_MTS_Covariance",
      "title": "A Funtion to generate a multivariate autoregressive process (MAR) model in time series. It is used for testing change-points based on the change in multivariate means or multivariate covariance for multivariate time series. It also works for the change in correlations between two univariate time series.",
      "topics": [
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      "page": "SNSeg",
      "title": "SNSeg: An R Package for Time Series Segmentation via Self-Normalization (SN)",
      "topics": [
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    {
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      "topics": [
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        "SN Test Statistic Plot: max_SNsweep",
        "Parameter Estimates of Each Segment Separated by the Detected Change-Points: SNSeg_estimate",
        "S3 methods: summary, print and plot",
        "Examples of SNSeg_Uni:",
        "Test in a single parameter",
        "Segmentation for Mean",
        "Segmentation for Variance",
        "Segmentation for Autocorrelation",
        "Segmentation for bivariate correlation",
        "Segmentation for quantile",
        "Test in a general functional",
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        "Examples: SNSeg_Multi",
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        "Segmentation for Multivariate Covariance",
        "Examples: SNSeg_HD"
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      "created": "2023-07-06 12:50:09",
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