# Holt-Winters method to develop a forecast for the non-seasonally adjusted monthly

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Holt-Winters method to develop a forecast for the non-seasonally adjusted monthly
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Purpose: Use the seasonal multiplicative
Holt-Winters method to develop a forecast for the non-seasonally adjusted
monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) for January
through December 2013. Note: the data is scaled in thousands of units.

Task: Use the tssmooth command with the
multiplicative seasonal Holt-Winters method to create a forecast of monthly
housing starts for January through December 2013, a monthly seasonal index, the
95% forecast confidence interval, a graph of the results, goodness-of-fit
measurements, and a chart of the forecast vs. actual values with upper and
lower 95% forecast intervals.

Directions:
UsingthemultiplicativeHolt-Wintersmethoddiscussedinclassandthenon-seasonallyadjusted
monthly Total: New Privately Owned Housing Units Started (HOUSTNSA) series from
the Federal Reserve FRED Economic Data and make a forecast for the next 12
months and provide the following information:

.
(1) The forecast for each of the 12 months
from January 2013 through December 2013.

.
(2) The 95% upper and lower forecast
confidence interval for each of the forecasted months.

.
(3) The seasonal index for each of the 12
seasonal periods (months).

.
(4) The mean squared error, root mean
squared error (mean absolute deviation), and percentage error of the in-sample
forecast error.

.
(5) The number and percentage of forecast
observations that fall outside of the upper and lower 95% forecast intervals.

(6) A chart of the actual vs. forecasted results
including the upper and lower 95% forecast interv

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