summary_argo {argo} | R Documentation |
performance summary of ARGO applied on CDC's ILI data
Description
performance summary of ARGO applied on CDC's ILI data
Usage
summary_argo(
GFT_xts,
model_names,
legend_names,
periods,
whole_period = "2009-03/2015-10"
)
Arguments
GFT_xts |
dataframe with all predicted values |
model_names |
name of predicting models |
legend_names |
legend for predicting models |
periods |
vector of periods to zoom into |
whole_period |
the whole period duration |
Value
A list of summary tables for the input periods, including RMSE, MAE, MAPE, corr
References
Yang, S., Santillana, M., & Kou, S. C. (2015). Accurate estimation of influenza epidemics using Google search data via ARGO. Proceedings of the National Academy of Sciences. <doi:10.1073/pnas.1515373112>. Shaoyang Ning, Shihao Yang, S. C. Kou. Accurate Regional Influenza Epidemics Tracking Using Internet Search Data. Scientific Reports
Examples
GFT_xts = xts::xts(exp(matrix(rnorm(1000), ncol=10)), order.by = Sys.Date() - (100:1))
names(GFT_xts) <- paste0("col", 1:10)
names(GFT_xts)[1] <- "CDC.data"
summary_argo(
GFT_xts = GFT_xts,
model_names = colnames(GFT_xts)[-1],
legend_names = paste0(colnames(GFT_xts)[-1], "legend"),
periods = c(paste0(zoo::index(GFT_xts)[1], "/", zoo::index(GFT_xts)[49]),
paste0(zoo::index(GFT_xts)[50], "/", zoo::index(GFT_xts)[100])),
whole_period="2009-03/"
)
[Package argo version 3.0.2 Index]