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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">INF1205</article-id><article-id pub-id-type="doi">10.3233/INF-1990-1205</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>General estimation of static model parameters and systematic measurement errors</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Nemura</surname><given-names>Antanas</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><aff id="j_INFORMATICA_aff_000">Institute for Physical and Engineering Problems of Energy Research, Lithuanian Academy of Sciences, 233684 Kaunas, Metalo St.4, Lithuania</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>1990</year></pub-date><volume>1</volume><issue>2</issue><fpage>87</fpage><lpage>95</lpage><abstract><p>The present paper considers the problem of general estimation of static model parameters and systematic measurement errors. The general estimation algorithm is based on static model linearization and on the least-squares method. The efficiency of this algorithm is illustrated by means of computer-aided digital simulation. The obtained equations and the algorithm of general estimation of static model parameters and systematic measurement errors can be applied for the solution of different practical problems. Estimatibility conditions must be satisfied in all cases.</p></abstract><kwd-group><label>Keywords</label><kwd>model linearization</kwd><kwd>least-squares estimates</kwd><kwd>recursive estimation</kwd></kwd-group></article-meta></front></article>