| aic5.ar.wge | Return top 5 AIC, AICC, or BIC picks for AR model fits |
| aic5.wge | Return top 5 AIC, AICC, or BIC picks |
| aic.ar.wge | AR Model Identification for AR models |
| aic.burg.wge | AR Model Identification using Burg Estimates |
| aic.wge | ARMA Model Identification |
| airline | Classical Airline Passenger Data |
| airlog | Natural log of airline data |
| appy | Non-perforated appendicitis data shown in Figure 10.8 (solid... |
| artrans.wge | Perform Ar transformations |
| backcast.wge | Calculate backcast residuals |
| bat | Bat echolocation signal shown in Figure 13.11a in Applied... |
| bitcoin | Daily Bitcoin Prices From May 1, 2020 to April 30, 2021 |
| Bsales | Toy Data Set of Business Sales Data |
| bumps16 | 16 point bumps signal |
| bumps256 | 256 point bumps signal |
| butterworth.wge | Perform Butterworth Filter |
| cardiac | Weekly Cardiac Mortality Data |
| cement | Cement data shown in Figure 3.30a in Applied Time Series... |
| chirp | Chirp data shown in Figure 12.2a in Applied Time Series... |
| co.wge | Cochrane-Orcutt test for trend |
| dfw.2011 | DFW Monthly Temperatures from January 2011 through December... |
| dfw.mon | DFW Monthly Temperatures |
| dfw.yr | DFW Annual Temperatures |
| doppler | Doppler Data |
| doppler2 | Doppler signal in Figure 13.10 in Applied Time Series... |
| dow1000 | Dow Jones daily rate of return data for 1000 days |
| dow1985 | Daily DOW Closing Prices 1985 through 2020 |
| dow.annual | DOW Annual Closing Averages |
| dowjones2014 | Dow Jones daily averages for 2014 |
| dow.rate | DOW Daily Rate of Return Data |
| eco.cd6 | 6-month rates |
| eco.corp.bond | Corporate bond rates |
| eco.mort30 | 30 year mortgage rates |
| est.arma.wge | Function to calculate ML estimates of parameters of... |
| est.ar.wge | Estimate parameters of an AR(p) model |
| est.farma.wge | Estimate the parameters of a FARMA model. |
| est.garma.wge | Estimate the parameters of a GARMA model. |
| est.glambda.wge | Estimate the value of lambda and offset to produce a... |
| expsmooth.wge | Exponential Smoothing |
| factor.comp.wge | Create a factor table and AR components for an AR realization |
| factor.wge | Produce factor table for a kth order AR or MA model |
| fig10.11x | Simulated data shown in Figure 10.11 (solid line) in Applied... |
| fig10.11y | Simulated data shown in Figure 10.11 (dashed line) in Applied... |
| fig10.1bond | Data for Figure 10.1b in Applied Time Series Analysis with R,... |
| fig10.1cd | Data shown in Figure 10.1a in Applied Time Series Analysis... |
| fig10.1mort | Data shown in Figure 10.1c in Applied Time Series Analysis... |
| fig10.3x1 | Variable X1 for the bivariate realization shown in Figure... |
| fig10.3x2 | Variable X2 for the bivariate realization shown in Figure... |
| fig1.10a | Simulated data shown in Figure 1.10a in Applied Time Series... |
| fig1.10b | Simulated data shown in Figure 1.10b in Applied Time Series... |
| fig1.10c | Simulated data in Figure 1.10c in Applied Time Series... |
| fig1.10d | Simulated data in Figure 1.10d in Applied Time Series... |
| fig11.12 | Data shown in Figure 11.12a in Applied Time Series Analysis... |
| fig11.4a | Data shown in Figure 11.4a in Applied Time Series Analysis... |
| fig1.16a | Simulated data for Figure 1.16a in Applied Time Series... |
| fig1.21a | Simulated shown in Figure 1.21a of Woodward, Gray, and... |
| fig12.1a | Simulated data with two frequencies shown in Figure 12.1a in... |
| fig12.1b | Simulated data with two frequencies shown in Figure 12.1b in... |
| fig1.22a | White noise data |
| fig13.18a | Simulated data shown in Figure 3.18a in Applied Time Series... |
| fig13.2c | TVF data shown in Figure 13.2c in Applied Time Series... |
| fig1.5 | Simulated data shown in Figure 1.5 in Applied Time Series... |
| fig3.10d | AR(2) Realization (1-.95)^2X(t)=a(t) |
| fig3.16a | Figure 3.16a in "Applied Time Series Analysis with R, 2nd... |
| fig3.18a | Figure 3.18a in "Applied Time Series Analysis with R, 2nd... |
| fig3.24a | ARMA(2,1) realization |
| fig3.29a | Simulated data shown in Figure 3.29a in Applied Time Series... |
| fig4.8a | Gaussian White Noise |
| fig5.3c | Data from Figure 5.3c in "Applied Time Series Analysis with... |
| fig6.11a | Cyclical Data |
| fig6.1nf | Data in Figure 6.1 without the forecasts |
| fig6.2nf | Data in Figure 6.2 without the forecasts |
| fig6.5nf | Data in Figure 6.5 without the forecasts |
| fig6.6nf | Data in Figure 6.6 without the forecasts |
| fig6.7nf | Data in Figure 6.2 without the forecasts |
| fig6.8nf | Simulated seasonal data with s=12 |
| fig8.11a | Data for Figure 8.11a in Applied Time Series Analysis with R,... |
| fig8.4a | Data for Figure 8.4a in Applied time series Analysis with R,... |
| fig8.6a | Data for Figure 8.6a in Applied time series Analysis with R,... |
| fig8.8a | Data for Figure 8.8a in Applied time series Analysis with R,... |
| flu | Influenza data shown in Figure 10.8 (dotted line) |
| fore.arima.wge | Function for forecasting from known model which may have... |
| fore.arma.wge | Forecast from known model |
| fore.aruma.wge | Function for forecasting from known model which may have... |
| fore.farma.wge | Forecast using a FARMA model |
| fore.garma.wge | Forecast using a GARMA model |
| fore.glambda.wge | Forecast using a G(lambda) model |
| fore.sigplusnoise.wge | Forecasting signal plus noise models |
| freeze | Minimum temperature data |
| freight | Freight data |
| gegenb.wge | Calculates Gegenbauer polynomials |
| gen.arch.wge | Generate a realization from an ARCH(q0) model |
| gen.arima.wge | Function to generate an ARIMA (or ARMA) realization |
| gen.arma.wge | Function to generate an ARMA realization |
| gen.aruma.wge | Function to generate an ARUMA (or ARMA or ARIMA) realization |
| gen.garch.wge | Generate a realization from a GARCH(p0,q0) model |
| gen.garma.wge | Function to generate a GARMA realization |
| gen.geg.wge | Function to generate a Gegenbauer realization |
| gen.glambda.wge | Function to generate a g(lambda) realization |
| gen.sigplusnoise.wge | Generate data from a signal-plus-noise model |
| global2020 | Global Temperature Data: 1880-2009 |
| global.temp | Global Temperature Data: 1850-2009 |
| hadley | Global temperature data |
| hilbert.wge | Function to calculate the Hilbert transformation of a given... |
| is.glambda.wge | Instantaneous spectrum |
| is.sample.wge | Sample instantaneous spectrum based on periodogram |
| kalman.miss.wge | Kalman filter for simple signal plus noise model with missing... |
| kalman.wge | Kalman filter for simple signal plus noise model |
| kingkong | King Kong Eats Grass |
| lavon | Lavon lake water levels |
| lavon15 | Lavon Lake Levels to September 30, 2015 |
| linearchirp | Linear chirp data. |
| ljung.wge | Ljung-Box Test |
| llynx | Log (base 10) of lynx data |
| lynx | Lynx data |
| ma2.table7.1 | Simulated MA(2) data |
| macoef.geg.wge | Calculate coefficients of the general linear process form of... |
| ma.pred.wge | Predictive or rolling moving average |
| ma.smooth.wge | Centered Moving Average Smoother |
| mass.mountain | Massachusettts Mountain Earthquake Data |
| MedDays | Median days a house stayed on the market |
| mm.eq | Massachusetts Mountain Earthquake data shown in Figure 13.13a... |
| mult.wge | Multiply Factors |
| NAICS | Monthly Retail Sales Data |
| nbumps256 | 256 noisy bumps signal |
| nile.min | Annual minimal water levels of Nile river |
| noctula | Nyctalus noctula echolocation data |
| NSA | Monthly Total Vehicle Sales |
| ozona | Daily Number of Chicken-Fried Steaks Sold |
| pacfts.wge | Compute partial autocorrelations |
| parzen.wge | Smoothed Periodogram using Parzen Window |
| patemp | Pennsylvania average monthly temperatures |
| period.wge | Calculate the periodogram |
| pi.weights.wge | Calculate pi weights for an ARMA model |
| plotts.dwt.wge | Plots Discrete Wavelet Transform (DWT) |
| plotts.mra.wge | Plots MRA plot) |
| plotts.parzen.wge | Calculate and plot the periodogram and Parzen window... |
| plotts.sample.wge | Plot Data, Sample Autocorrelations, Periodogram, and Parzen... |
| plotts.true.wge | Plot of generated data, true autocorrelations and true... |
| plotts.wge | Plot a time series realization |
| prob10.4 | Data matrix for Problem 10.4 in "Applied Time Series Analysis... |
| prob10.6x | Data for Problem 10.6 in Applied Time Series Analysis with R,... |
| prob10.6y | Simulated observed data for Problem 10.6 in Applied Time... |
| prob10.7x | Data for Problem 10.7 in Applied Time Series Analysis with R,... |
| prob10.7y | Simulated observed data for Problem 10.6 in Applied Time... |
| prob11.5 | Data for Problem 11.5 in Applied Time Series Analysis with R,... |
| prob12.1c | Data for Problem 12.1c and 12.3c in Applied Time Series... |
| prob12.3a | Data for Problem 12.3a in Applied Time Series Analysis with... |
| prob12.3b | Data for Problem 12.3b in Applied Time Series Analysis with... |
| prob12.6c | Data set for Problem 12.6(C) in Applied Time Series Analysis... |
| prob13.2 | Data for Problem 13.2 in Applied Time Series Analysis with R,... |
| prob8.1a | Data for Problem 8.1 in "Applied Time Series Analysis with R,... |
| prob8.1b | Data for Problem 8.1 in "Applied Time Series Analysis with R,... |
| prob8.1c | Data for Problem 8.1 in "Applied Time Series Analysis with R,... |
| prob8.1d | Data for Problem 8.1 in "Applied Time Series Analysis with R,... |
| prob9.6c1 | Data set 1 for Problem 6.1c |
| prob9.6c2 | Data set 2 for Problem 6.1c |
| prob9.6c3 | Data set 3 for Problem 6.1c |
| prob9.6c4 | Data set 4 for Problem 6.1c |
| psi.weights.wge | Calculate psi weights for an ARMA model |
| rate | Daily DOW rate of Return |
| roll.win.rmse.nn.wge | Function to Calculate the Rolling Window RMSE |
| roll.win.rmse.wge | Function to Calculate the Rolling Window RMSE |
| sample.spec.wge | Smoothed Periodogram using Parzen Window |
| slr.wge | Simple Linear Regression |
| ss08 | Sunspot Data |
| ss08.1850 | Sunspot data from 1850 through 2008 for matching with global... |
| starwort.ex | Starwort Explosion data shown in Figure 13.13a in Applied... |
| sunspot2.0 | Annual Sunspot2.0 Numbers |
| sunspot2.0.month | Monthly Sunspot2.0 Numbers |
| sunspot.classic | Classic Sunspot Data: 1749-1924 |
| table10.1.noise | Noise related to data set, the first 5 points of which are... |
| table10.1.signal | Underlying, unobservable signal (X(t), the first 5 points of... |
| table7.1 | MA(2) data for Table 7.1 |
| tesla | Tesla Stock Prices |
| trans.to.dual.wge | Transforms TVF data set to a dual data set |
| trans.to.original.wge | Transforms dual data set back to original time scale |
| true.arma.aut.wge | True ARMA autocorrelations |
| true.arma.spec.wge | True ARMA Spectral Density |
| true.farma.aut.wge | True FARMA autocorrelations |
| true.garma.aut.wge | True GARMA autocorrelations |
| tswge-package | Time Series package for Woodward, Gray, and Elliott text |
| tx.unemp.adj | Texas Seasonally Adjusted Unnemployment Rates |
| tx.unemp.unadj | Texas Unadjusted Unnemployment Rates |
| unit.circle.wge | Plot the roots of the characteristic equation on the complex... |
| uspop | US population |
| us.retail | Quarterly US Retail Sales |
| wages | Daily wages in Pounds from 1260 to 1944 for England |
| wbg.boot.wge | Woodward-Bottone-Gray test for trend |
| whale | Whale click data |
| wtcrude | West Texas Intermediate Crude Oil Prices |
| wtcrude2020 | Monthly WTI Crude Oil Prices |
| wv.wge | Function to calculate Wigner Ville spectrum |
| yellowcab.precleaned | Precleaned Yellow Cab data |
