accuracy.default | Accuracy measures for a forecast model |
Acf | (Partial) Autocorrelation and Cross-Correlation Function... |
arfima | Fit a fractionally differenced ARFIMA model |
Arima | Fit ARIMA model to univariate time series |
arima.errors | Errors from a regression model with ARIMA errors |
arimaorder | Return the order of an ARIMA or ARFIMA model |
auto.arima | Fit best ARIMA model to univariate time series |
autolayer | Create a ggplot layer appropriate to a particular data type |
autoplot.acf | ggplot (Partial) Autocorrelation and Cross-Correlation... |
autoplot.seas | Plot time series decomposition components using ggplot |
autoplot.ts | Automatically create a ggplot for time series objects |
baggedModel | Forecasting using a bagged model |
bats | BATS model (Exponential smoothing state space model with... |
bizdays | Number of trading days in each season |
bld.mbb.bootstrap | Box-Cox and Loess-based decomposition bootstrap. |
BoxCox | Box Cox Transformation |
BoxCox.lambda | Automatic selection of Box Cox transformation parameter |
checkresiduals | Check that residuals from a time series model look like white... |
croston | Forecasts for intermittent demand using Croston's method |
CV | Cross-validation statistic |
CVar | k-fold Cross-Validation applied to an autoregressive model |
dm.test | Diebold-Mariano test for predictive accuracy |
dshw | Double-Seasonal Holt-Winters Forecasting |
easter | Easter holidays in each season |
ets | Exponential smoothing state space model |
findfrequency | Find dominant frequency of a time series |
fitted.Arima | h-step in-sample forecasts for time series models. |
forecast.Arima | Forecasting using ARIMA or ARFIMA models |
forecast.baggedModel | Forecasting using a bagged model |
forecast.bats | Forecasting using BATS and TBATS models |
forecast.ets | Forecasting using ETS models |
forecast.HoltWinters | Forecasting using Holt-Winters objects |
forecast.lm | Forecast a linear model with possible time series components |
forecast.mlm | Forecast a multiple linear model with possible time series... |
forecast.modelAR | Forecasting using user-defined model |
forecast.mts | Forecasting time series |
forecast.nnetar | Forecasting using neural network models |
forecast-package | forecast: Forecasting Functions for Time Series and Linear... |
forecast.stl | Forecasting using stl objects |
forecast.StructTS | Forecasting using Structural Time Series models |
forecast.ts | Forecasting time series |
fourier | Fourier terms for modelling seasonality |
gas | Australian monthly gas production |
geom_forecast | Forecast plot |
getResponse | Get response variable from time series model. |
gghistogram | Histogram with optional normal and kernel density functions |
gglagplot | Time series lag ggplots |
ggmonthplot | Create a seasonal subseries ggplot |
gold | Daily morning gold prices |
is.constant | Is an object constant? |
is.ets | Is an object a particular model type? |
is.forecast | Is an object a particular forecast type? |
ma | Moving-average smoothing |
meanf | Mean Forecast |
modelAR | Time Series Forecasts with a user-defined model |
modeldf | Compute model degrees of freedom |
monthdays | Number of days in each season |
mstl | Multiple seasonal decomposition |
msts | Multi-Seasonal Time Series |
na.interp | Interpolate missing values in a time series |
naive | Naive and Random Walk Forecasts |
ndiffs | Number of differences required for a stationary series |
nnetar | Neural Network Time Series Forecasts |
nsdiffs | Number of differences required for a seasonally stationary... |
ocsb.test | Osborn, Chui, Smith, and Birchenhall Test for Seasonal Unit... |
plot.Arima | Plot characteristic roots from ARIMA model |
plot.bats | Plot components from BATS model |
plot.ets | Plot components from ETS model |
plot.forecast | Forecast plot |
plot.mforecast | Multivariate forecast plot |
reexports | Objects exported from other packages |
residuals.forecast | Residuals for various time series models |
seasadj | Seasonal adjustment |
seasonal | Extract components from a time series decomposition |
seasonaldummy | Seasonal dummy variables |
seasonplot | Seasonal plot |
ses | Exponential smoothing forecasts |
simulate.ets | Simulation from a time series model |
sindexf | Forecast seasonal index |
splinef | Cubic Spline Forecast |
subset.ts | Subsetting a time series |
taylor | Half-hourly electricity demand |
tbats | TBATS model (Exponential smoothing state space model with... |
tbats.components | Extract components of a TBATS model |
thetaf | Theta method forecast |
tsclean | Identify and replace outliers and missing values in a time... |
tsCV | Time series cross-validation |
tsdisplay | Time series display |
tslm | Fit a linear model with time series components |
tsoutliers | Identify and replace outliers in a time series |
wineind | Australian total wine sales |
woolyrnq | Quarterly production of woollen yarn in Australia |
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