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SUMMARY:QLS Seminar: Entropy and statistical complexity rates of Student's
t-process
DTSTART;VALUE=DATE-TIME:20230906T120000Z
DTEND;VALUE=DATE-TIME:20230906T130000Z
DTSTAMP;VALUE=DATE-TIME:20241014T195935Z
UID:indico-event-10528@ictp.it
DESCRIPTION:Abstract:\n Student's t-process is a parametrized generalizati
on of the Gaussian process\, which is widely used for the analysis of heav
y-tailed data. Although these processes share several principal properties
\, an important difference can be observed once their Renyi entropy rates
are analyzed instead of the commonly considered Shannon entropy rate. In t
his talk\, we show that stationary Student's t-processes have\, in general
\, a nonfinite Renyi entropy rate\, while a specific class of nonstationar
y Student's t-processes has a finite Renyi entropy rate\, which is fully o
pposed to the Shannon case. After that\, we extend considerations to the g
eneralized statistical complexity rates\, which represent an interplay bet
ween order and disorder levels of a random process. We show that the stati
stical complexity rates are invariant with respect to the stationarity of
the Student's t-process while keeping information about its shape paramete
r.\n\n \n \n\n//indico.ictp.it/event/10528/
LOCATION:ICTP Common Area\, ex SISSA building\, second floor
URL://indico.ictp.it/event/10528/
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