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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">ipolytech</journal-id><journal-title-group><journal-title xml:lang="ru">iPolytech Journal</journal-title><trans-title-group xml:lang="en"><trans-title>iPolytech Journal</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2782-4004</issn><issn pub-type="epub">2782-6341</issn><publisher><publisher-name>Irkutsk National Research Technical University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21285/1814-3520-2018-6-120-128</article-id><article-id custom-type="elpub" pub-id-type="custom">ipolytech-114</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ИНФОРМАТИКА, ВЫЧИСЛИТЕЛЬНАЯ ТЕХНИКА И УПРАВЛЕНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>INFORMATION SCIENCE, COMPUTER ENGINEERING AND CONTROL</subject></subj-group></article-categories><title-group><article-title>ИССЛЕДОВАНИЕ ДЕГРАДАЦИОННЫХ ГАММА-МОДЕЛЕЙ СО СЛУЧАЙНЫМ И ФИКСИРОВАННЫМ ЭФФЕКТАМИ</article-title><trans-title-group xml:lang="en"><trans-title>STUDY OF FIXED EFFECT AND RANDOM EFFECT GAMMA DEGRADATION MODELS</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Четвертакова</surname><given-names>Е. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Chetvertakova</surname><given-names>E. S.</given-names></name></name-alternatives><email xlink:type="simple">evgenia.chetvertakova@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Новосибирский государственный технический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Novosibirsk State Technical University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2018</year></pub-date><pub-date pub-type="epub"><day>15</day><month>09</month><year>2020</year></pub-date><volume>22</volume><issue>6</issue><fpage>120</fpage><lpage>128</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Четвертакова Е.С., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Четвертакова Е.С.</copyright-holder><copyright-holder xml:lang="en">Chetvertakova E.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://ipolytech.elpub.ru/jour/article/view/114">https://ipolytech.elpub.ru/jour/article/view/114</self-uri><abstract><p>ЦЕЛЬ. Построение деградационной модели со случайным эффектом приводит к увеличению размерности вектора оцениваемых параметров, поэтому необходимо выяснить, позволяет ли введение случайного эффекта получить более точные оценки параметров модели. В данной статье проводится сравнение точности оценок параметров деградационных гамма-моделей со случайным и фиксированным эффектами. МЕТОДЫ. Исследование точности оценок максимального правдоподобия параметров деградационных моделей проводится путем вычисления Евклидовой нормы относительной погрешности получаемых оценок для различной величины случайного эффекта с использованием метода Монте-Карло. РЕЗУЛЬТАТЫ И ИХ ОБСУЖДЕНИЕ. С ростом величины случайного эффекта точность оценивания параметров повышается для деградационной гамма-модели со случайным эффектом. Однако в случае, когда показатель разброса значений деградационного показателя относительно заданной функции тренда не превышает 0.1, для достижения большей точности оценок параметров модели целесообразно использовать деградационную гамма-модель с фиксированным эффектом. ВЫВОДЫ. Показано, что использование деградационной гамма-модели со случайным эффектом нецелесообразно при работе с небольшими объемами выборок и незначительном случайном эффекте.</p></abstract><trans-abstract xml:lang="en"><p>PURPOSE. Construction of the random effect gamma degradation model results in the enlarged dimension of the vector of estimated parameters. Therefore, it is necessary to understand whether the introduction of the random effect allows to obtain more accurate estimates of model parameters or not. The paper compares the fixed effect and random effect gamma degradation models in terms of the estimation accuracy of their parameters. METHODS. The estimation accuracy of the highest likelihood of degradation model parameters is studied through the calculation of the Euclidean norm of the relative error of the obtained estimates for the different values of random effect based on the Monte-Carlo method. RESULTS AND THEIR DISCUSSION. The estimation accuracy of parameters is higher for the random effect degradation model with the increase of the random effect value. However, if unit-to-unit variability coefficient does not exceed 0.1, it is recommended to use the fixed effect degradation model for the higher estimation accuracy of model parameters. MAIN CONCLUSIONS. It is shown that the use of the random effect gamma degradation model is not advisable in the case of small sample volumes and an insignificant random effect.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>деградационный процесс</kwd><kwd>деградационная гамма-модель</kwd><kwd>модель со случайным эффектом</kwd><kwd>надежность</kwd><kwd>метод Монте-Карло</kwd></kwd-group><kwd-group xml:lang="en"><kwd>degradation process</kwd><kwd>gamma degradation model</kwd><kwd>random effect model</kwd><kwd>reliability</kwd><kwd>Monte Carlo method</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Антонов А.В., Никулин М.С. Статистические модели в теории надежности // М.: Абрис, 2012. 390 с.</mixed-citation><mixed-citation xml:lang="en">Антонов А.В., Никулин М.С. 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