{
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  "Package": "simts",
  "Type": "Package",
  "Title": "Time Series Analysis Tools",
  "Version": "0.2.4",
  "LazyData": "true",
  "Authors@R": "c(\nperson(\"Stéphane\", \"Guerrier\", email = \"stef.guerrier@gmail.com\", role = c(\"aut\",\"cre\",\"cph\")),\nperson(\"James\", \"Balamuta\", role = c(\"aut\",\"cph\")),\nperson(\"Roberto\", \"Molinari\", role = c(\"aut\",\"cph\")),\nperson(\"Justin\", \"Lee\", role = \"aut\"),\nperson(\"Lionel\", \"Voirol\", role = \"aut\"),\nperson(\"Yuming\", \"Zhang\", role = \"aut\"),\nperson(\"Wenchao\", \"Yang\", role = \"ctb\"),\nperson(\"Nathanael\", \"Claussen\", role = \"ctb\"),\nperson(\"Yunxiang\", \"Zhang\", role = \"ctb\"),\nperson(\"Christian\", \"Gunning\", role = \"cph\"),\nperson(\"Romain\", \"Francois\", role = \"cph\"),\nperson(\"Ross\", \"Ihaka\", role = \"cph\"),\nperson(\"R Core Team\", role = \"cph\")\n)",
  "Maintainer": "Stéphane Guerrier <stef.guerrier@gmail.com>",
  "Description": "A system contains easy-to-use tools as a support for time\nseries analysis courses. In particular, it incorporates a\ntechnique called Generalized Method of Wavelet Moments (GMWM)\nas well as its robust implementation for fast and robust\nparameter estimation of time series models which is described,\nfor example, in Guerrier et al. (2013) <doi:\n10.1080/01621459.2013.799920>. More details can also be found\nin the paper linked to via the URL below.",
  "License": "AGPL-3 | file LICENSE",
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  "URL": "https://github.com/SMAC-Group/simts,\nhttps://arxiv.org/pdf/1607.04543.pdf",
  "BugReports": "https://github.com/SMAC-Group/simts/issues",
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  "Repository": "https://smac-group.r-universe.dev",
  "Date/Publication": "2026-03-10 08:59:08 UTC",
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  "_topics": [
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    "rcpparmadillo",
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  "_homeurl": "https://github.com/smac-group/simts",
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  "_releases": [
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      "date": "2019-07-19"
    },
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    {
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  "_exports": [
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    "AR1",
    "ar1_to_gm",
    "ARIMA",
    "ARMA",
    "ARMA11",
    "auto_corr",
    "best_model",
    "check",
    "comb",
    "compare_acf",
    "conv.ar1.to.gm",
    "conv.gm.to.ar1",
    "corr_analysis",
    "create_imu",
    "desc.to.ts.model",
    "diag_boxpierce",
    "diag_ljungbox",
    "DR",
    "estimate",
    "evaluate",
    "FGN",
    "gen_ar1",
    "gen_ar1blocks",
    "gen_arima",
    "gen_arma",
    "gen_arma11",
    "gen_bi",
    "gen_dr",
    "gen_fgn",
    "gen_generic_sarima",
    "gen_gts",
    "gen_lts",
    "gen_lts_cpp",
    "gen_ma1",
    "gen_matern",
    "gen_mean",
    "gen_model",
    "gen_nswn",
    "gen_powerlaw",
    "gen_qn",
    "gen_rw",
    "gen_sarima",
    "gen_sarma",
    "gen_sin",
    "gen_wn",
    "GM",
    "gm_to_ar1",
    "gmwm",
    "gmwm_master_cpp",
    "gts",
    "gts_time",
    "has",
    "imu",
    "is.gts",
    "is.imu",
    "is.lts",
    "is.ts.model",
    "is.whole",
    "lts",
    "M",
    "MA",
    "Ma_cpp",
    "Ma_cpp_vec",
    "MA1",
    "make_frame",
    "MAPE",
    "MAT",
    "model_objdesc",
    "model_process_desc",
    "model_theta",
    "np_boot_sd_med",
    "orderModel",
    "PLP",
    "QN",
    "RW",
    "RW2dimension",
    "SARIMA",
    "SARMA",
    "select",
    "select_ar",
    "select_arima",
    "select_arma",
    "select_ma",
    "SIN",
    "theo_acf",
    "theo_pacf",
    "unitConversion",
    "update_obj",
    "value",
    "WN"
  ],
  "_datasets": [
    {
      "name": "australia",
      "title": "Quarterly Increase in Stocks Non-Farm Total, Australia",
      "object": "australia",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "Quarter",
        "Increase"
      ],
      "rows": 127,
      "table": true,
      "tojson": true
    },
    {
      "name": "hydro",
      "title": "Mean Monthly Precipitation, from 1907 to 1972",
      "object": "hydro",
      "class": [
        "ts"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "savingrt",
      "title": "Personal Saving Rate",
      "object": "savingrt",
      "class": [
        "gts",
        "matrix"
      ],
      "fields": [
        "US Personal Saving Rates"
      ],
      "rows": 691,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "sub-.imu",
      "title": "Subset an IMU Object",
      "topics": [
        "[.imu"
      ]
    },
    {
      "page": "AIC.fitsimts",
      "title": "Akaike's Information Criterion",
      "topics": [
        "AIC.fitsimts"
      ]
    },
    {
      "page": "AR",
      "title": "Create an Autoregressive P [AR(P)] Process",
      "topics": [
        "AR"
      ]
    },
    {
      "page": "AR1",
      "title": "Definition of an Autoregressive Process of Order 1",
      "topics": [
        "AR1"
      ]
    },
    {
      "page": "ar1_to_wv",
      "title": "AR(1) process to WV",
      "topics": [
        "ar1_to_wv"
      ]
    },
    {
      "page": "ARIMA",
      "title": "Create an Autoregressive Integrated Moving Average (ARIMA) Process",
      "topics": [
        "ARIMA"
      ]
    },
    {
      "page": "ARMA",
      "title": "Create an Autoregressive Moving Average (ARMA) Process",
      "topics": [
        "ARMA"
      ]
    },
    {
      "page": "arma_to_wv",
      "title": "ARMA process to WV",
      "topics": [
        "arma_to_wv"
      ]
    },
    {
      "page": "ARMA11",
      "title": "Definition of an ARMA(1,1)",
      "topics": [
        "ARMA11"
      ]
    },
    {
      "page": "arma11_to_wv",
      "title": "ARMA(1,1) to WV",
      "topics": [
        "arma11_to_wv"
      ]
    },
    {
      "page": "australia",
      "title": "Quarterly Increase in Stocks Non-Farm Total, Australia",
      "topics": [
        "australia"
      ]
    },
    {
      "page": "auto_corr",
      "title": "Empirical ACF and PACF",
      "topics": [
        "auto_corr"
      ]
    },
    {
      "page": "best_model",
      "title": "Select the Best Model",
      "topics": [
        "best_model"
      ]
    },
    {
      "page": "check",
      "title": "Diagnostics on Fitted Time Series Model",
      "topics": [
        "check"
      ]
    },
    {
      "page": "compare_acf",
      "title": "Comparison of Classical and Robust Correlation Analysis Functions",
      "topics": [
        "compare_acf"
      ]
    },
    {
      "page": "corr_analysis",
      "title": "Correlation Analysis Functions",
      "topics": [
        "corr_analysis"
      ]
    },
    {
      "page": "deriv_2nd_ar1",
      "title": "Analytic second derivative matrix for AR(1) process",
      "topics": [
        "deriv_2nd_ar1"
      ]
    },
    {
      "page": "deriv_2nd_arma11",
      "title": "Analytic D matrix for ARMA(1,1) process",
      "topics": [
        "deriv_2nd_arma11"
      ]
    },
    {
      "page": "deriv_2nd_dr",
      "title": "Analytic second derivative matrix for drift process",
      "topics": [
        "deriv_2nd_dr"
      ]
    },
    {
      "page": "deriv_2nd_ma1",
      "title": "Analytic second derivative for MA(1) process",
      "topics": [
        "deriv_2nd_ma1"
      ]
    },
    {
      "page": "deriv_ar1",
      "title": "Analytic D matrix for AR(1) process",
      "topics": [
        "deriv_ar1"
      ]
    },
    {
      "page": "deriv_arma11",
      "title": "Analytic D matrix for ARMA(1,1) process",
      "topics": [
        "deriv_arma11"
      ]
    },
    {
      "page": "deriv_dr",
      "title": "Analytic D matrix for Drift (DR) Process",
      "topics": [
        "deriv_dr"
      ]
    },
    {
      "page": "deriv_ma1",
      "title": "Analytic D matrix for MA(1) process",
      "topics": [
        "deriv_ma1"
      ]
    },
    {
      "page": "deriv_qn",
      "title": "Analytic D matrix for Quantization Noise (QN) Process",
      "topics": [
        "deriv_qn"
      ]
    },
    {
      "page": "deriv_rw",
      "title": "Analytic D matrix Random Walk (RW) Process",
      "topics": [
        "deriv_rw"
      ]
    },
    {
      "page": "deriv_wn",
      "title": "Analytic D Matrix for a Gaussian White Noise (WN) Process",
      "topics": [
        "deriv_wn"
      ]
    },
    {
      "page": "derivative_first_matrix",
      "title": "Analytic D matrix of Processes",
      "topics": [
        "derivative_first_matrix"
      ]
    },
    {
      "page": "diag_boxpierce",
      "title": "Box-Pierce",
      "topics": [
        "diag_boxpierce"
      ]
    },
    {
      "page": "diag_ljungbox",
      "title": "Ljung-Box",
      "topics": [
        "diag_ljungbox"
      ]
    },
    {
      "page": "diag_plot",
      "title": "Diagnostic Plot of Residuals",
      "topics": [
        "diag_plot"
      ]
    },
    {
      "page": "diag_portmanteau_",
      "title": "Portmanteau Tests",
      "topics": [
        "diag_portmanteau_"
      ]
    },
    {
      "page": "DR",
      "title": "Create an Drift (DR) Process",
      "topics": [
        "DR"
      ]
    },
    {
      "page": "dr_to_wv",
      "title": "Drift to WV",
      "topics": [
        "dr_to_wv"
      ]
    },
    {
      "page": "estimate",
      "title": "Fit a Time Series Model to Data",
      "topics": [
        "estimate"
      ]
    },
    {
      "page": "evaluate",
      "title": "Evalute a time series or a list of time series models",
      "topics": [
        "evaluate"
      ]
    },
    {
      "page": "FGN",
      "title": "Definition of a Fractional Gaussian Noise (FGN) Process",
      "topics": [
        "FGN"
      ]
    },
    {
      "page": "gen_ar1blocks",
      "title": "Generate AR(1) Block Process",
      "topics": [
        "gen_ar1blocks"
      ]
    },
    {
      "page": "gen_bi",
      "title": "Generate Bias-Instability Process",
      "topics": [
        "gen_bi"
      ]
    },
    {
      "page": "gen_gts",
      "title": "Simulate a simts TS object using a theoretical model",
      "topics": [
        "gen_gts"
      ]
    },
    {
      "page": "gen_lts",
      "title": "Generate a Latent Time Series Object Based on a Model",
      "topics": [
        "gen_lts"
      ]
    },
    {
      "page": "gen_nswn",
      "title": "Generate Non-Stationary White Noise Process",
      "topics": [
        "gen_nswn"
      ]
    },
    {
      "page": "GM",
      "title": "Create a Gauss-Markov (GM) Process",
      "topics": [
        "GM"
      ]
    },
    {
      "page": "gmwm",
      "title": "Generalized Method of Wavelet Moments (GMWM)",
      "topics": [
        "gmwm"
      ]
    },
    {
      "page": "gmwm_imu",
      "title": "GMWM for (Robust) Inertial Measurement Units (IMUs)",
      "topics": [
        "gmwm_imu"
      ]
    },
    {
      "page": "gts",
      "title": "Create a simts TS object using time series data",
      "topics": [
        "gts"
      ]
    },
    {
      "page": "hydro",
      "title": "Mean Monthly Precipitation, from 1907 to 1972",
      "topics": [
        "hydro"
      ]
    },
    {
      "page": "imu",
      "title": "Create an IMU Object",
      "topics": [
        "imu"
      ]
    },
    {
      "page": "imu_time",
      "title": "Pulls the IMU time from the IMU object",
      "topics": [
        "imu_time"
      ]
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