This function transforms daily crime count data and plots the resultant components of a time series which has been decomposed into seasonal, trend, and irregular components using Loess smoothing. Holt Winters exponential smoothing is also performed for inproved trend resolution since data is in a daily format.
Data frame of crime or RMS data. See provided Chicago Data Portal example for reference
Start date for the time series being analyzed. The format is as follows: c('year', 'month', 'day'). See example below for reference.
Returns an object of class "stl" with the following components:
time.series: a multiple time series with columns seasonal, trend and remainder.
weights: the final robust weights (all one if fitting is not done robustly).
call: the matched call.
win: integer (length 3 vector) with the spans used for the "s", "t", and "l" smoothers.
deg: integer (length 3) vector with the polynomial degrees for these smoothers.
jump: integer (length 3) vector with the 'jumps' (skips) used for these smoothers.
inner: number of inner iterations
Jamie Spaulding, Keith Morris
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