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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">INFORMATICA</journal-id><journal-title-group><journal-title>Informatica</journal-title></journal-title-group><issn pub-type="epub">0868-4952</issn><issn pub-type="ppub">0868-4952</issn><publisher><publisher-name>VU</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">INF2103</article-id><article-id pub-id-type="doi">10.3233/INF-1991-2103</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>Likelihood inference about a change point in switching autoregression</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Kligienė</surname><given-names>Nerutė</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><aff id="j_INFORMATICA_aff_000">Institute of Mathematics and Informatics, Lithuanian Academy of Sciences, 232600 Vilnius, Akademijos St.4, Lithuania</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>1991</year></pub-date><volume>2</volume><issue>1</issue><fpage>53</fpage><lpage>65</lpage><abstract><p>A likelihood approach is considered to the problem of making inferences about the point t = ν in a Gaussian autoregressive sequence {X<inf>t</inf>, t = 1 ÷ N} at which the underlying AR(p) parameters undergo a sudden change. The statistics of a loglikelihood function L(n, ν) is investigated over the admissible values n ∈ (p + 1, <formula>$\dots$</formula> , N - 1) of a change point ν under validity of hypothesis of a change and no change. The expressions of L(n, ν) implying the loss of plausibility when moving away from the true change point ν are presented, and the probabilities P{<formula>$\bar{v}_{N}$</formula> = ν± r}, r = 0,1,2, <formula>$\dots$</formula>, where <formula>$\bar{v}_{N}$</formula> is the MLH estimate of a change point ν from the available realization x<inf>1</inf>,x<inf>2</inf>,…,x<inf>N</inf> of {X<inf>t</inf>, t = 1 ÷ N} are considered.</p></abstract><kwd-group><label>Keywords</label><kwd>change point problem</kwd><kwd>likelihood inference</kwd><kwd>autoregressive sequences</kwd></kwd-group></article-meta></front></article>