I am working with four different time series which have the same first and last dates, but a different number of observations. One time series (svq) includes weekend data, the other three don't include weekend data, but seem to be missing a few days each. I can get the Intersection of "Dates" common to all four series and map each index over the common dates to get a matching set of values, but that is perhaps not the best way to get those values. Can someone suggest a better way?
$\begingroup$
$\endgroup$
Compare and contrast the following example series:
ts1 = TimeSeries[{1, 2, 3, 4}, {{1, 2, 3, 4}}]
ts1 // ListLinePlot[#, Mesh -> Full] &
ts2 = TimeSeries[{5, 4, 3, 2, 1}, {{1, 1.3, 2, 3.5, 4}}];
ts2 // ListLinePlot[#, Mesh -> Full] &
Using
TimeSeriesResample[{ts1, ts2}, "Intersection"] // ListLinePlot[#, Mesh -> Full] &
we obtain the values at common dates:
TimeSeriesResample[{<time series>}, "Intersection"]
$\endgroup$ – user42582 May 16 '18 at 19:49TimeSeriesResample
until I read this question; that's the reason I like mma.se; it forces you to be honest with what you know and learn the rest $\endgroup$ – user42582 May 16 '18 at 20:40TimeSeriesResample[ ts , {starttime,endtime,"BusinessDay"}
also worked. $\endgroup$ – George Wolfe May 17 '18 at 20:14