<?xml version="1.0" encoding="UTF-8"?>
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<title>Jos M K</title>
<link href="http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/448" rel="alternate"/>
<subtitle/>
<id>http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/448</id>
<updated>2026-04-29T02:29:12Z</updated>
<dc:date>2026-04-29T02:29:12Z</dc:date>
<entry>
<title>HARRIS PROCESSES</title>
<link href="http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/449" rel="alternate"/>
<author>
<name>Sebastian, Sherly</name>
</author>
<author>
<name>Jos, M. K</name>
</author>
<author>
<name>Sandhya, E</name>
</author>
<author>
<name>Raju, N</name>
</author>
<id>http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/449</id>
<updated>2025-02-12T06:20:30Z</updated>
<published>2005-11-01T00:00:00Z</published>
<summary type="text">HARRIS PROCESSES
Sebastian, Sherly; Jos, M. K; Sandhya, E; Raju, N
In this paper, we develop two stochastic models where the variable under consideration&#13;
follows Harris distribution. The mean and variance of the processes are derived and the&#13;
processes are shown to be non-stationary. In the second model, starting with a Poisson&#13;
process, an alternate way of obtaining Harris process is introduced.
</summary>
<dc:date>2005-11-01T00:00:00Z</dc:date>
</entry>
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