Template-Type: ReDIF-Paper 1.0
Title: Markovian interval processes I: Nonparametric inference
Author-Name: Klaus J. Utikal
Classification-JEL: C13, C14
Keywords: counting process regression, nonparametric functional estimation,
 intensity, Markov process, renewal process, martingale central limit
 theorem, sequential Aalen estimator, kernel function smoothing,
 goodness-of-fit test
Abstract: Consider a p-variate counting process N = (...) with jump times {...}.
 Suppose that the intensity of jumps ... of ... at time t depends on the
 other components, i. e. ..., where the ... are unknown, nonrandom functions.
    From observing one single trajectory of the processes N over an
 increasing interval of time we estimate nonparametrically the functions ...
 The estimators are shown to be uniformly consistent over compact sets. We
 derive a nonparametric asymptotic test for the hypothesis that ... does not
 depend on ... i. e. that ... is a renewal process. In Part II the results
 obtained are applied in the analysis of simultaneous neuronal spike train
 series.
Series:	Sonderforschungsbereich 303, University of Bonn, Germany
Length: 23 pages
Creation-Date: 1990-09
Revision-Date: 
Handle: RePEc:bon:bonsfa:486