Made sd the default weight in forecast.gts, and added the HLW referen…

…ce in a couple of other man files
earowang · Jun 10, 2014 · e7ce48b · e7ce48b
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Showing 5 changed files with 14 additions and 3 deletions.
diff --git a/ChangeLog b/ChangeLog
@@ -4,6 +4,7 @@ v4.3 (10 June 2014)
 * Improved arg "characters" in hts() to automate the node structure.
 * Added a new arg "characters" in gts(), which will automate the grouping matrix.
 * Added a new reference to combinef() man.
+* Made 'sd' the default weight in forecast.gts().
 
 v4.2 (25 Mar 2014)
 * Fixed Next.Generic error in accuracy.gts.

diff --git a/R/forecast.gts.R b/R/forecast.gts.R
@@ -5,7 +5,7 @@ forecast.gts <- function(object, h = ifelse(frequency(object) > 1L,
                          fmethod = c("ets", "arima", "rw"), 
                          keep.fitted = FALSE, keep.resid = FALSE,
                          positive = FALSE, lambda = NULL, level, 
-                         weights = c("none", "sd", "nseries"),
+                         weights = c("sd", "none", "nseries"),
                          parallel = FALSE, num.cores = 2,
                          xreg = NULL, newxreg = NULL, ...) {
   # Forecast hts or gts objects

diff --git a/man/combinef.Rd b/man/combinef.Rd
@@ -22,7 +22,6 @@ Optimal combination forecasts for hierarchical time series.
 \emph{Computational Statistics and Data Analysis}, \bold{55}(9), 2579--2589.
 \url{http://robjhyndman.com/papers/hierarchical/}
 
-
 Hyndman, R. J., Lee, A., & Wang, E. (2014). 
 Fast computation of reconciled forecasts for hierarchical and grouped time series. 
 \emph{Working paper 17/14, Department of Econometrics & Business Statistics, Monash University.}

diff --git a/man/forecast.gts.Rd b/man/forecast.gts.Rd
@@ -14,7 +14,7 @@ Methods for forecasting hierarchical or grouped time series.
                          fmethod = c("ets", "arima", "rw"), 
                          keep.fitted = FALSE, keep.resid = FALSE,
                          positive = FALSE, lambda = NULL, level, 
-                         weights = c("none", "sd", "nseries"),
+                         weights = c("sd", "none", "nseries"),
                          parallel = FALSE, num.cores = 2,
                          xreg = NULL, newxreg = NULL, ...) 
 }
@@ -55,6 +55,11 @@ Optimal combination forecasts for hierarchical time series.
 \emph{Computational Statistics and Data Analysis}, \bold{55}(9), 2579--2589.
 \url{http://robjhyndman.com/papers/hierarchical/}
 
+Hyndman, R. J., Lee, A., & Wang, E. (2014). 
+Fast computation of reconciled forecasts for hierarchical and grouped time series. 
+\emph{Working paper 17/14, Department of Econometrics & Business Statistics, Monash University.}
+\url{http://robjhyndman.com/working-papers/hgts/}
+
 Gross, C. and Sohl, J. (1990) Dissagregation methods to expedite product line forecasting,
 \emph{Journal of Forecasting}, \bold{9}, 233-254.
 }

diff --git a/man/hts-package.Rd b/man/hts-package.Rd
@@ -19,6 +19,12 @@ R. J. Hyndman, R. A. Ahmed, G. Athanasopoulos and H.L. Shang (2011)
 Optimal combination forecasts for hierarchical time series. 
 \emph{Computational Statistics and Data Analysis}, \bold{55}(9), 2579--2589.
 \url{http://robjhyndman.com/papers/hierarchical/}
+
+
+Hyndman, R. J., Lee, A., & Wang, E. (2014). 
+Fast computation of reconciled forecasts for hierarchical and grouped time series. 
+\emph{Working paper 17/14, Department of Econometrics & Business Statistics, Monash University.}
+\url{http://robjhyndman.com/working-papers/hgts/}
 }
 \keyword{package}