@misc{epub1503,
volume = {114},
abstract = {We are dealing with series of events occurring at random times tau\verb1_1n and carrying further quantitive information xi\verb1_1n . Examples are sequences of extrasystoles in ECG\-records. We will present two approaches for analyzing such (typically long) sequences (tau\verb1_1n, xi\verb1_1n ), n = 1, 2, ... . (i) A point process model is based on an intensity of the form alpha(t) * b\verb1_1t(theta), t >= 0, with b\verb1_1t a stochastic intensity of the self\-exciting type. (ii) A time series approach is based on a transitional GLM. The conditional expectation of the waiting time sigma\verb1_1\verb1{1n+1\verb1}1 = tau\verb1_1\verb1{1n+1\verb1}1 - tau\verb1_1n is set to be v(tau\verb1_1n) * h(eta\verb1_1n(theta)), with h a response function and eta\verb1_1n a regression term. The deterministic functions alpha and v, respectively, describe the long-term trend of the process.},
title = {Semiparametric Point Process and Time Series Models for Series of Events},
author = {H. Pruscha},
year = {1998},
series = {sfb386},
url = {http://nbn-resolving.de/urn/resolver.pl?urn=nbn:de:bvb:19-epub-1503-0}
}