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    {
      "page": "bitcoin",
      "title": "Daily Bitcoin Prices From May 1, 2020 to April 30, 2021",
      "topics": [
        "bitcoin"
      ]
    },
    {
      "page": "Bsales",
      "title": "Toy Data Set of Business Sales Data",
      "topics": [
        "Bsales"
      ]
    },
    {
      "page": "bumps16",
      "title": "16 point bumps signal",
      "topics": [
        "bumps16"
      ]
    },
    {
      "page": "bumps256",
      "title": "256 point bumps signal",
      "topics": [
        "bumps256"
      ]
    },
    {
      "page": "butterworth.wge",
      "title": "Perform Butterworth Filter",
      "topics": [
        "butterworth.wge"
      ]
    },
    {
      "page": "cardiac",
      "title": "Weekly Cardiac Mortality Data",
      "topics": [
        "cardiac"
      ]
    },
    {
      "page": "cement",
      "title": "Cement data shown in Figure 3.30a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "cement"
      ]
    },
    {
      "page": "chirp",
      "title": "Chirp data shown in Figure 12.2a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "chirp"
      ]
    },
    {
      "page": "co.wge",
      "title": "Cochrane-Orcutt test for trend",
      "topics": [
        "co.wge"
      ]
    },
    {
      "page": "dfw.2011",
      "title": "DFW Monthly Temperatures from January 2011 through December 2020",
      "topics": [
        "dfw.2011"
      ]
    },
    {
      "page": "dfw.mon",
      "title": "DFW Monthly Temperatures",
      "topics": [
        "dfw.mon"
      ]
    },
    {
      "page": "dfw.yr",
      "title": "DFW Annual Temperatures",
      "topics": [
        "dfw.yr"
      ]
    },
    {
      "page": "doppler",
      "title": "Doppler Data",
      "topics": [
        "doppler"
      ]
    },
    {
      "page": "doppler2",
      "title": "Doppler signal in Figure 13.10 in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "doppler2"
      ]
    },
    {
      "page": "dow.annual",
      "title": "DOW Annual Closing Averages",
      "topics": [
        "dow.annual"
      ]
    },
    {
      "page": "dow.rate",
      "title": "DOW Daily Rate of Return Data",
      "topics": [
        "dow.rate"
      ]
    },
    {
      "page": "dow1000",
      "title": "Dow Jones daily rate of return data for 1000 days",
      "topics": [
        "dow1000"
      ]
    },
    {
      "page": "dow1985",
      "title": "Daily DOW Closing Prices 1985 through 2020",
      "topics": [
        "dow1985"
      ]
    },
    {
      "page": "dowjones2014",
      "title": "Dow Jones daily averages for 2014",
      "topics": [
        "dowjones2014"
      ]
    },
    {
      "page": "eco.cd6",
      "title": "6-month rates",
      "topics": [
        "eco.cd6"
      ]
    },
    {
      "page": "eco.corp.bond",
      "title": "Corporate bond rates",
      "topics": [
        "eco.corp.bond"
      ]
    },
    {
      "page": "eco.mort30",
      "title": "30 year mortgage rates",
      "topics": [
        "eco.mort30"
      ]
    },
    {
      "page": "est.ar.wge",
      "title": "Estimate parameters of an AR(p) model",
      "topics": [
        "est.ar.wge"
      ]
    },
    {
      "page": "est.arma.wge",
      "title": "Function to calculate ML estimates of parameters of stationary ARMA models",
      "topics": [
        "est.arma.wge"
      ]
    },
    {
      "page": "est.farma.wge",
      "title": "Estimate the parameters of a FARMA model.",
      "topics": [
        "est.farma.wge"
      ]
    },
    {
      "page": "est.garma.wge",
      "title": "Estimate the parameters of a GARMA model.",
      "topics": [
        "est.garma.wge"
      ]
    },
    {
      "page": "est.glambda.wge",
      "title": "Estimate the value of lambda and offset to produce a stationary dual.",
      "topics": [
        "est.glambda.wge"
      ]
    },
    {
      "page": "expsmooth.wge",
      "title": "Exponential Smoothing",
      "topics": [
        "expsmooth.wge"
      ]
    },
    {
      "page": "factor.comp.wge",
      "title": "Create a factor table and AR components for an AR realization",
      "topics": [
        "factor.comp.wge"
      ]
    },
    {
      "page": "factor.wge",
      "title": "Produce factor table for a kth order AR or MA model",
      "topics": [
        "factor.wge"
      ]
    },
    {
      "page": "fig1.10a",
      "title": "Simulated data shown in Figure 1.10a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.10a"
      ]
    },
    {
      "page": "fig1.10b",
      "title": "Simulated data shown in Figure 1.10b in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.10b"
      ]
    },
    {
      "page": "fig1.10c",
      "title": "Simulated data in Figure 1.10c in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.10c"
      ]
    },
    {
      "page": "fig1.10d",
      "title": "Simulated data in Figure 1.10d in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.10d"
      ]
    },
    {
      "page": "fig1.16a",
      "title": "Simulated data for Figure 1.16a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.16a"
      ]
    },
    {
      "page": "fig1.21a",
      "title": "Simulated shown in Figure 1.21a of Woodward, Gray, and Elliott text",
      "topics": [
        "fig1.21a"
      ]
    },
    {
      "page": "fig1.22a",
      "title": "White noise data",
      "topics": [
        "fig1.22a"
      ]
    },
    {
      "page": "fig1.5",
      "title": "Simulated data shown in Figure 1.5 in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig1.5"
      ]
    },
    {
      "page": "fig10.11x",
      "title": "Simulated data shown in Figure 10.11 (solid line) in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig10.11x"
      ]
    },
    {
      "page": "fig10.11y",
      "title": "Simulated data shown in Figure 10.11 (dashed line) in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig10.11y"
      ]
    },
    {
      "page": "fig10.1bond",
      "title": "Data for Figure 10.1b in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig10.1bond"
      ]
    },
    {
      "page": "fig10.1cd",
      "title": "Data shown in Figure 10.1a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig10.1cd"
      ]
    },
    {
      "page": "fig10.1mort",
      "title": "Data shown in Figure 10.1c in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig10.1mort"
      ]
    },
    {
      "page": "fig10.3x1",
      "title": "Variable X1 for the bivariate realization shown in Figure 10.3\"",
      "topics": [
        "fig10.3x1"
      ]
    },
    {
      "page": "fig10.3x2",
      "title": "Variable X2 for the bivariate realization shown in Figure 10.3\"",
      "topics": [
        "fig10.3x2"
      ]
    },
    {
      "page": "fig11.12",
      "title": "Data shown in Figure 11.12a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig11.12"
      ]
    },
    {
      "page": "fig11.4a",
      "title": "Data shown in Figure 11.4a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig11.4a"
      ]
    },
    {
      "page": "fig12.1a",
      "title": "Simulated data with two frequencies shown in Figure 12.1a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig12.1a"
      ]
    },
    {
      "page": "fig12.1b",
      "title": "Simulated data with two frequencies shown in Figure 12.1b in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig12.1b"
      ]
    },
    {
      "page": "fig13.18a",
      "title": "Simulated data shown in Figure 3.18a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig13.18a"
      ]
    },
    {
      "page": "fig13.2c",
      "title": "TVF data shown in Figure 13.2c in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig13.2c"
      ]
    },
    {
      "page": "fig3.10d",
      "title": "AR(2) Realization (1-.95)^2X(t)=a(t)",
      "topics": [
        "fig3.10d"
      ]
    },
    {
      "page": "fig3.16a",
      "title": "Figure 3.16a in \"Applied Time Series Analysis with R, 2nd edition\" by Woodward, Gray, and Elliott",
      "topics": [
        "fig3.16a"
      ]
    },
    {
      "page": "fig3.18a",
      "title": "Figure 3.18a in \"Applied Time Series Analysis with R, 2nd edition\" by Woodward, Gray, and Elliott",
      "topics": [
        "fig3.18a"
      ]
    },
    {
      "page": "fig3.24a",
      "title": "ARMA(2,1) realization",
      "topics": [
        "fig3.24a"
      ]
    },
    {
      "page": "fig3.29a",
      "title": "Simulated data shown in Figure 3.29a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig3.29a"
      ]
    },
    {
      "page": "fig4.8a",
      "title": "Gaussian White Noise",
      "topics": [
        "fig4.8a"
      ]
    },
    {
      "page": "fig5.3c",
      "title": "Data from Figure 5.3c in \"Applied Time Series Analysis with R, 2nd edition\" by Woodward, Gray, and Elliott",
      "topics": [
        "fig5.3c"
      ]
    },
    {
      "page": "fig6.11a",
      "title": "Cyclical Data",
      "topics": [
        "fig6.11a"
      ]
    },
    {
      "page": "fig6.1nf",
      "title": "Data in Figure 6.1 without the forecasts",
      "topics": [
        "fig6.1nf"
      ]
    },
    {
      "page": "fig6.2nf",
      "title": "Data in Figure 6.2 without the forecasts",
      "topics": [
        "fig6.2nf"
      ]
    },
    {
      "page": "fig6.5nf",
      "title": "Data in Figure 6.5 without the forecasts",
      "topics": [
        "fig6.5nf"
      ]
    },
    {
      "page": "fig6.6nf",
      "title": "Data in Figure 6.6 without the forecasts",
      "topics": [
        "fig6.6nf"
      ]
    },
    {
      "page": "fig6.7nf",
      "title": "Data in Figure 6.2 without the forecasts",
      "topics": [
        "fig6.7nf"
      ]
    },
    {
      "page": "fig6.8nf",
      "title": "Simulated seasonal data with s=12",
      "topics": [
        "fig6.8nf"
      ]
    },
    {
      "page": "fig8.11a",
      "title": "Data for Figure 8.11a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig8.11a"
      ]
    },
    {
      "page": "fig8.4a",
      "title": "Data for Figure 8.4a in Applied time series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig8.4a"
      ]
    },
    {
      "page": "fig8.6a",
      "title": "Data for Figure 8.6a in Applied time series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig8.6a"
      ]
    },
    {
      "page": "fig8.8a",
      "title": "Data for Figure 8.8a in Applied time series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "fig8.8a"
      ]
    },
    {
      "page": "flu",
      "title": "Influenza data shown in Figure 10.8 (dotted line)",
      "topics": [
        "flu"
      ]
    },
    {
      "page": "fore.arima.wge",
      "title": "Function for forecasting from known model which may have (1-B)^d and/or seasonal factors",
      "topics": [
        "fore.arima.wge"
      ]
    },
    {
      "page": "fore.arma.wge",
      "title": "Forecast from known model",
      "topics": [
        "fore.arma.wge"
      ]
    },
    {
      "page": "fore.aruma.wge",
      "title": "Function for forecasting from known model which may have (1-B)^d, seasonal, and/or other nonstationary factors",
      "topics": [
        "fore.aruma.wge"
      ]
    },
    {
      "page": "fore.farma.wge",
      "title": "Forecast using a FARMA model",
      "topics": [
        "fore.farma.wge"
      ]
    },
    {
      "page": "fore.garma.wge",
      "title": "Forecast using a GARMA model",
      "topics": [
        "fore.garma.wge"
      ]
    },
    {
      "page": "fore.glambda.wge",
      "title": "Forecast using a G(lambda) model",
      "topics": [
        "fore.glambda.wge"
      ]
    },
    {
      "page": "fore.sigplusnoise.wge",
      "title": "Forecasting signal plus noise models",
      "topics": [
        "fore.sigplusnoise.wge"
      ]
    },
    {
      "page": "freeze",
      "title": "Minimum temperature data",
      "topics": [
        "freeze"
      ]
    },
    {
      "page": "freight",
      "title": "Freight data",
      "topics": [
        "freight"
      ]
    },
    {
      "page": "gegenb.wge",
      "title": "Calculates Gegenbauer polynomials",
      "topics": [
        "gegenb.wge"
      ]
    },
    {
      "page": "gen.arch.wge",
      "title": "Generate a realization from an ARCH(q0) model",
      "topics": [
        "gen.arch.wge"
      ]
    },
    {
      "page": "gen.arima.wge",
      "title": "Function to generate an ARIMA (or ARMA) realization",
      "topics": [
        "gen.arima.wge"
      ]
    },
    {
      "page": "gen.arma.wge",
      "title": "Function to generate an ARMA realization",
      "topics": [
        "gen.arma.wge"
      ]
    },
    {
      "page": "gen.aruma.wge",
      "title": "Function to generate an ARUMA (or ARMA or ARIMA) realization",
      "topics": [
        "gen.aruma.wge"
      ]
    },
    {
      "page": "gen.garch.wge",
      "title": "Generate a realization from a GARCH(p0,q0) model",
      "topics": [
        "gen.garch.wge"
      ]
    },
    {
      "page": "gen.garma.wge",
      "title": "Function to generate a GARMA realization",
      "topics": [
        "gen.garma.wge"
      ]
    },
    {
      "page": "gen.geg.wge",
      "title": "Function to generate a Gegenbauer realization",
      "topics": [
        "gen.geg.wge"
      ]
    },
    {
      "page": "gen.glambda.wge",
      "title": "Function to generate a g(lambda) realization",
      "topics": [
        "gen.glambda.wge"
      ]
    },
    {
      "page": "gen.sigplusnoise.wge",
      "title": "Generate data from a signal-plus-noise model",
      "topics": [
        "gen.sigplusnoise.wge"
      ]
    },
    {
      "page": "global.temp",
      "title": "Global Temperature Data: 1850-2009",
      "topics": [
        "global.temp"
      ]
    },
    {
      "page": "global2020",
      "title": "Global Temperature Data: 1880-2009",
      "topics": [
        "global2020"
      ]
    },
    {
      "page": "hadley",
      "title": "Global temperature data",
      "topics": [
        "hadley"
      ]
    },
    {
      "page": "hilbert.wge",
      "title": "Function to calculate the Hilbert transformation of a given real valued signal(even length)",
      "topics": [
        "hilbert.wge"
      ]
    },
    {
      "page": "is.glambda.wge",
      "title": "Instantaneous spectrum",
      "topics": [
        "is.glambda.wge"
      ]
    },
    {
      "page": "is.sample.wge",
      "title": "Sample instantaneous spectrum based on periodogram",
      "topics": [
        "is.sample.wge"
      ]
    },
    {
      "page": "kalman.miss.wge",
      "title": "Kalman filter for simple signal plus noise model with missing data",
      "topics": [
        "kalman.miss.wge"
      ]
    },
    {
      "page": "kalman.wge",
      "title": "Kalman filter for simple signal plus noise model",
      "topics": [
        "kalman.wge"
      ]
    },
    {
      "page": "kingkong",
      "title": "King Kong Eats Grass",
      "topics": [
        "kingkong"
      ]
    },
    {
      "page": "lavon",
      "title": "Lavon lake water levels",
      "topics": [
        "lavon"
      ]
    },
    {
      "page": "lavon15",
      "title": "Lavon Lake Levels to September 30, 2015",
      "topics": [
        "lavon15"
      ]
    },
    {
      "page": "linearchirp",
      "title": "Linear chirp data.",
      "topics": [
        "linearchirp"
      ]
    },
    {
      "page": "ljung.wge",
      "title": "Ljung-Box Test",
      "topics": [
        "ljung.wge"
      ]
    },
    {
      "page": "llynx",
      "title": "Log (base 10) of lynx data",
      "topics": [
        "llynx"
      ]
    },
    {
      "page": "lynx",
      "title": "Lynx data",
      "topics": [
        "lynx"
      ]
    },
    {
      "page": "ma.pred.wge",
      "title": "Predictive or rolling moving average",
      "topics": [
        "ma.pred.wge"
      ]
    },
    {
      "page": "ma.smooth.wge",
      "title": "Centered Moving Average Smoother",
      "topics": [
        "ma.smooth.wge"
      ]
    },
    {
      "page": "ma2.table7.1",
      "title": "Simulated MA(2) data",
      "topics": [
        "ma2.table7.1"
      ]
    },
    {
      "page": "macoef.geg.wge",
      "title": "Calculate coefficients of the general linear process form of a Gegenbauer process",
      "topics": [
        "macoef.geg.wge"
      ]
    },
    {
      "page": "mass.mountain",
      "title": "Massachusettts Mountain Earthquake Data",
      "topics": [
        "mass.mountain"
      ]
    },
    {
      "page": "MedDays",
      "title": "Median days a house stayed on the market",
      "topics": [
        "MedDays"
      ]
    },
    {
      "page": "mm.eq",
      "title": "Massachusetts Mountain Earthquake data shown in Figure 13.13a in Applied Time Series Analysis with R, second edition by Woodward, Gray, and Elliott",
      "topics": [
        "mm.eq"
      ]
    },
    {
      "page": "mult.wge",
      "title": "Multiply Factors",
      "topics": [
        "mult.wge"
      ]
    },
    {
      "page": "NAICS",
      "title": "Monthly Retail Sales Data",
      "topics": [
        "NAICS"
      ]
    },
    {
      "page": "nbumps256",
      "title": "256 noisy bumps signal",
      "topics": [
        "nbumps256"
      ]
    },
    {
      "page": "nile.min",
      "title": "Annual minimal water levels of Nile river",
      "topics": [
        "nile.min"
      ]
    },
    {
      "page": "noctula",
      "title": "Nyctalus noctula echolocation data",
      "topics": [
        "noctula"
      ]
    },
    {
      "page": "NSA",
      "title": "Monthly Total Vehicle Sales",
      "topics": [
        "NSA"
      ]
    },
    {
      "page": "ozona",
      "title": "Daily Number of Chicken-Fried Steaks Sold",
      "topics": [
        "ozona"
      ]
    },
    {
      "page": "pacfts.wge",
      "title": "Compute partial autocorrelations",
      "topics": [
        "pacfts.wge"
      ]
    },
    {
      "page": "parzen.wge",
      "title": "Smoothed Periodogram using Parzen Window",
      "topics": [
        "parzen.wge"
      ]
    },
    {
      "page": "patemp",
      "title": "Pennsylvania average monthly temperatures",
      "topics": [
        "patemp"
      ]
    },
    {
      "page": "period.wge",
      "title": "Calculate the periodogram",
      "topics": [
        "period.wge"
      ]
    },
    {
      "page": "pi.weights.wge",
      "title": "Calculate pi weights for an ARMA model",
      "topics": [
        "pi.weights.wge"
      ]
    },
    {
      "page": "plotts.dwt.wge",
      "title": "Plots Discrete Wavelet Transform (DWT)",
      "topics": [
        "plotts.dwt.wge"
      ]
    },
    {
      "page": "plotts.mra.wge",
      "title": "Plots MRA plot)",
      "topics": [
        "plotts.mra.wge"
      ]
    },
    {
      "page": "plotts.parzen.wge",
      "title": "Calculate and plot the periodogram and Parzen window estimates with differing trunctaion points",
      "topics": [
        "plotts.parzen.wge"
      ]
    },
    {
      "page": "plotts.sample.wge",
      "title": "Plot Data, Sample Autocorrelations, Periodogram, and Parzen Spectral Estimate",
      "topics": [
        "plotts.sample.wge"
      ]
    },
    {
      "page": "plotts.true.wge",
      "title": "Plot of generated data, true autocorrelations and true spectral density for ARMA model",
      "topics": [
        "plotts.true.wge"
      ]
    },
    {
      "page": "plotts.wge",
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