On Jan 8, 2012, at 3:01 AM, Iasonas Lamprianou wrote:
Dear all,
I am not sure if this is the right place to ask this question, but I
will have a go. Please redirect me to a different place if this is
not the right one!
I have a (relatively) simple problem which causes me some
frustration because I cannot find the solution. I measure ten
variables (var1 to var10) every day, they are all continuous
(linear) and most of them are correlated. Some days, for any reason,
the relationship between these variables may change. They are still
correlated, but their correlation may change slightly but
practically this is important. Or, one of the variables may increase
its value significantly suddenly and keep this high value for a few
days and then come back to the normal level. I am using R. Is there
any function I can use to help me identify these strange days when
the relationship between these variables changes? For example, if
DayX is such a strange day, factor analyzing the data before DayX
and after DayX separately would give me different factors (princial
components). But how can I identify such a daym without trial and
error?
The zoo package has `rollapply`. You would of course be required to be
much more specific in defining your problem than you have been so far.
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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