"forecast"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"forecast"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent", "vector", "bootstrap-recurrent", "bootstrap-vector"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
"predict"(object, groups, len = 1, method = c("recurrent-column", "recurrent-row", "vector-column", "vector-row"), ..., drop = TRUE, drop.attributes = FALSE, cache = TRUE)
level
argument to bforecast
)forecast
function call,
predicted series for predict
call.
Rssa
for an overview of the package, as well as,
rforecast
,
vforecast
,
bforecast
,
forecast (package)
s <- ssa(co2)
# Calculate 24-point forecast using first 6 components as a base
f <- forecast(s, groups = list(1:6), method = "bootstrap-recurrent", len = 24, R = 10)
# Plot the result including the last 24 points of the series
plot(f, include = 24, shadecols = "green", type = "l")
# Use of predict() for prediction
p <- predict(s, groups = list(1:6), method = "recurrent", len = 24)
# Simple plotting
plot(p, ylab = "Forecasteed Values")
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