Description Usage Arguments Examples
This function performs time series regression with seasonal considerations by computing the following (as per Dr. Chatterjee's instruction in Fall 2016): (centered) moving average, seasonl ratio, raw seasonal indices, normalized seasonal indices, de-seasonalized raw data, de-seasonalized predictions, and re-seasonalized predictions. Optionally, it can carry this forecasting method out past the end of the data set.
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data |
time series data. |
start |
the time of the first observation. Either a single number or a vector of two integers, which specify a natural time unit and a (1-based) number of samples into the time unit. See the examples for the use of the second form. |
end |
the time of the last observation, specified in the same way as start. |
frequency |
the number of observations per unit of time. |
plot.initial |
a boolean indicating whether you want a plot of the initial time series. |
df.print |
a boolean value indicating whether you want the data frame to be printed. |
no.predict |
the number of predictions to perform. |
mad |
whether to print mean absolute deviation. |
1 | csts()
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