Forecasting with R Training Course

Forecasting with R for Government

• Introduction to Forecasting for Government
• Exponential Smoothing Techniques for Government Applications
• ARIMA Models for Government Data Analysis
• The forecast Package for Government Use

Package 'forecast' for Government

• accuracy: Assessing Forecast Accuracy for Government Projects
• Acf: Autocorrelation Function for Government Data
• arfima: Fractional Differencing Models for Government Time Series
• Arima: Fitting ARIMA Models to Government Data
• arima.errors: Extracting Errors from ARIMA Models for Government Analysis
• auto.arima: Automated ARIMA Model Selection for Government Datasets
• bats: Exponential Smoothing State Space Model with Box-Cox Transformation, ARMA Errors, Trend and Seasonal Components for Government Use
• BoxCox: Applying Box-Cox Transformations to Government Data
• BoxCox.lambda: Estimating the Optimal Box-Cox Transformation Parameter for Government Datasets
• croston: Croston's Method for Intermittent Demand Forecasting in Government Settings
• CV: Cross-Validation for Model Selection in Government Applications
• dm.test: Diebold-Mariano Test for Comparing Forecast Accuracy in Government Projects
• dshw: Double Seasonal Holt-Winters Method for Government Time Series Analysis
• ets: Exponential Smoothing State Space Model for Government Data
• fitted.Arima: Extracting Fitted Values from ARIMA Models in Government Studies
• forecast: General Forecasting Function for Government Use
• forecast.Arima: Forecasting with ARIMA Models for Government Data
• forecast.bats: Forecasting with BATS Models for Government Applications
• forecast.ets: Forecasting with ETS Models for Government Datasets
• forecast.HoltWinters: Forecasting with Holt-Winters Models for Government Analysis
• forecast.lm: Forecasting Using Linear Models in Government Projects
• forecast.stl: Forecasting with STL Decomposition for Government Data
• forecast.StructTS: Forecasting with Structural Time Series Models for Government Use
• gas: Gas Consumption Dataset for Government Analysis
• gold: Gold Price Dataset for Government Studies
• logLik.ets: Log-Likelihood of ETS Models for Government Data
• ma: Moving Average Smoothing for Government Time Series
• meanf: Mean Forecasting Method for Government Applications
• monthdays: Number of Days in Each Month for Government Use
• msts: Multiple Seasonal Time Series for Government Data Analysis
• na.interp: Interpolating Missing Values in Government Datasets
• naive: Naive Forecasting Method for Government Studies
• ndiffs: Number of Differences Required for Stationarity in Government Time Series
• nnetar: Neural Network Time Series Forecasts for Government Data
• plot.bats: Plotting BATS Model Diagnostics for Government Analysis
• plot.ets: Plotting ETS Model Diagnostics for Government Datasets
• plot.forecast: Plotting Forecast Results for Government Use
• rwf: Random Walk with Drift Forecasting Method for Government Applications
• seasadj: Seasonal Adjustment of Time Series Data for Government Analysis
• seasonaldummy: Seasonal Dummy Variables for Government Time Series Models
• seasonplot: Seasonal Plotting for Government Datasets
• ses: Simple Exponential Smoothing for Government Data Analysis
• simulate.ets: Simulating from ETS Models for Government Studies
• sindexf: Seasonal Index Forecasting for Government Applications
• splinef: Spline Forecasting Method for Government Data
• subset.ts: Subsetting Time Series Data for Government Analysis
• taylor: Taylor's Hourly Electricity Demand Dataset for Government Studies
• tbats: TBATS Model for Complex Seasonal Time Series in Government Use
• thetaf: Theta Method Forecasting for Government Data Analysis
• tsdisplay: Displaying Time Series Plots and Diagnostics for Government Datasets
• tslm: Linear Model Fitting to Time Series Data for Government Use
• wineind: Australian Wine Sales Dataset for Government Analysis
• woolyrnq: Quarterly Wool Production in Australia Dataset for Government Studies

Summary and Next Steps for Government