#
# Simulate an example
#
x.test <- tvar2sim()
#
# Do a two-step ahead forecast
#
x.fl <- forecastlpacf(x.test, h=2, forecast.type="recursive")
#
# Print out the object
#
print(x.fl)
#
# This is what gets output
#
#Class 'forecastlpacf' : Forecast from Locally Stationary Time Series:
# ~~~~ : List with 8 components with names
# mean std.err lpacf ci binwidth p x d
#
#
#summary(.):
#----------
#Number of steps ahead predicted: 2
#Predictions are (3dp): 1.52 -0.365
#Std err are (3dp): 0.952 0.955
#Smoothing binwidth was: 293
#Forecast was based on a p-backlag value selected as: 3
#There was no explicit differencing.
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