more theta tests and start on theta plot method

pkg/DESCRIPTION

@@ -1,6 +1,6 @@
 Package: forecastHybrid
 Title: Convenient Functions for Ensemble Time Series Forecasts
-Version: 0.3.0
+Version: 0.3.1.9000
 Date: 2016-09-23
 Authors@R: c(
    person("David", "Shaub", email = "davidshaub@gmx.com", role = c("aut", "cre")),

pkg/R/theta.R

@@ -12,6 +12,9 @@
 #' used in \code{hybridModel()}.
 #' @return An object of class \code{thetam}
 #' @author Peter Ellis
+#' @examples 
+#' mod1 <- thetam(Nile)
+#' plot(mod1)
 #' @seealso \code{\link{forecast.thetam}}
 thetam <- function(y){
    n <- length(y)
@@ -41,7 +44,7 @@ thetam <- function(y){
    object$x <- origy
    object$drift <- stats::lsfit(0:(n - 1), y)$coef[2] / 2
    object$method <- "Theta"
-   class(object) <- "thetam"
+   class(object) <- c("thetam")
 
    return(object)
 }
@@ -56,6 +59,10 @@ thetam <- function(y){
 #' @param level Confidence level for prediction intervals
 #' @param fan If TRUE, level is set to \code{seq(51, 99, by = 3)}. This is suitable for fan plots.
 #' @return An object of class \code{forecast}
+#' @examples
+#' mod1 <- thetam(Nile)
+#' fc1 <- forecast(mod1)
+#' plot(fc1)
 #' @author Peter Ellis
 #' @seealso \code{\link{thetam}}
 forecast.thetam <- function(object, h = ifelse(object$m > 1, 2 * object$m, 10), 
@@ -85,4 +92,17 @@ forecast.thetam <- function(object, h = ifelse(object$m > 1, 2 * object$m, 10),
    return(fcast)
 }
 
+#' Plot components from Theta model
+#' 
+#' Produces a plot of the level components from the ETS model underlying a Theta model
+#' @export
+#' @param x Object of class "thetam".
+#' @author Peter Ellis
+plot.thetam <- function(x, ...){
+   y <- x$x
+   plot(cbind(observed = y, level = x$states[, 1]), 
+        main = paste("Decomposition by", x$method, "method"), ...)
+   #TODO - add the slope
+}
 
+# TODO - autoplot.thetam

pkg/inst/NEWS.md

@@ -1,5 +1,7 @@
 # Version 0.3.0 [Unreleased]
 * Prediction intervals are now created for `nnetar` objects in the ensemble. This should address one aspect of incorrect prediction intervals (e.g. issue #37).
+* theta models can be added (by including "`f`" in the `models=` argument for `hybridModel()`)
+* `accuracy.cvts` is exported
 
 # Version 0.2.0 [2016-09-23]
 * Add timeseries cross validation with `cvts()`

pkg/tests/testthat/test-theta.R

@@ -32,3 +32,14 @@ fan2 <- thetaf(AirPassengers, level = c(75, 90))
 expect_equal(sum(fan1$upper - fan2$upper), 0)
 expect_equal(sum(fan1$lower - fan2$lower), 0)
 
+# another example
+fc1 <- thetaf(Nile)
+fc2 <- forecast(thetam(Nile))
+expect_equal(sum(fc2$mean - fc1$mean), 0)
+expect_equal(sum(fc2$upper - fc1$upper), 0)
+expect_equal(sum(fc2$lower - fc1$lower), 0)
+
+fc3 <- forecast(thetam(Nile), level = c(0.7, 0.9))
+expect_equal(sum(fc3$mean - fc1$mean), 0)
+expect_lt(sum(fc3$upper - fc1$upper), 0)
+expect_gt(sum(fc3$lower - fc1$lower), 0)