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Файл:Eviews5 / EViews5 / Example Files / x12 / example6
.txt 9 February 1988
Example 6: Use of modelspan to facilitate finding an acceptable
model for an economist's index series. We could not
find a model with good diagnostics for the full series.
A graph of the log-transformed series suggests it has a
different growth rate after the first three years. An
acceptable model was found for the data span beginning
January, 1989. Note the improvements to all the
modeling diagnostics.
# Example 6: index0.spc
# An economist's index series. Difficult to find an acceptable model without
# a modelspan statement.
Series{
title = "Index Series Run with Full-Series Modeling"
file="index.dat"
start = 1986.jan
}
transform{ function=log }
regression{ variables=( AO1991.Apr ) }
arima{
model=([1,6] 1 0)(0 1 1)
}
estimate{ }
check{print=all}
forecast{ maxlead=36 }
# Example 6: index.spc
# Modelspan allows us to find an acceptable model for an economist's index series.
Series{
title = "Index Series Run using Modelspan"
file="index.dat"
start = 1986.jan
modelspan = (1989.jan,)
}
transform{ function=log }
regression{ variables=( AO1991.Apr ) }
arima{
model=([1,6] 1 0)(0 1 1)
}
estimate{ }
check{print=all}
forecast{ maxlead=36 }
Example 6: Use of modelspan to facilitate finding an acceptable
model for an economist's index series. We could not
find a model with good diagnostics for the full series.
A graph of the log-transformed series suggests it has a
different growth rate after the first three years. An
acceptable model was found for the data span beginning
January, 1989. Note the improvements to all the
modeling diagnostics.
# Example 6: index0.spc
# An economist's index series. Difficult to find an acceptable model without
# a modelspan statement.
Series{
title = "Index Series Run with Full-Series Modeling"
file="index.dat"
start = 1986.jan
}
transform{ function=log }
regression{ variables=( AO1991.Apr ) }
arima{
model=([1,6] 1 0)(0 1 1)
}
estimate{ }
check{print=all}
forecast{ maxlead=36 }
# Example 6: index.spc
# Modelspan allows us to find an acceptable model for an economist's index series.
Series{
title = "Index Series Run using Modelspan"
file="index.dat"
start = 1986.jan
modelspan = (1989.jan,)
}
transform{ function=log }
regression{ variables=( AO1991.Apr ) }
arima{
model=([1,6] 1 0)(0 1 1)
}
estimate{ }
check{print=all}
forecast{ maxlead=36 }
Соседние файлы в папке x12