Modeling and Forecasting Visitor Counts Using Social Media
trim training data
Automatic Decomposition Function
Check Arguments
convert_ts_forecast_to_df
Decompose Popularity Proxy
Estimate Lag Function
Estimate Parameters for Visitation Model
Visitation Model
Converting Annual Counts into Monthly Counts
Fit Model
Generate Proxy Trend Forecasts
Imputation
labeled_visitation_forecast Class
"decomposition" Constructor Function
visitation_forecast_ensemble Class
visitation_forecast Class
"visitation_model" Constructor Function
Decomposition Plot Methods
visitation_model visitation_forecast_ensemble plot Methods
visitation_forecast Plot Methods
visitation_model Plot Methods
Predict Decomposition
Predict Visitation Model
Notify User prediction warning on constant is 0
Decomposition Summary Method
visitation_forecast Summary Method
visitation_model Summary Method
Decomposition Summary Method
visitation_forecast Summary Method
visitation_model Summary Method
Performs modeling and forecasting of park visitor counts using social media data and (partial) on-site visitor counts. Specifically, the model is built based on an automatic decomposition of the trend and seasonal components of the social media-based park visitor counts, from which short-term forecasts of the visitor counts and percent changes in the visitor counts can be made. A reference for the underlying model that 'VisitorCounts' uses can be found at Russell Goebel, Austin Schmaltz, Beth Ann Brackett, Spencer A. Wood, Kimihiro Noguchi (2023) <doi:10.1002/for.2965> .