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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">mireabulletin</journal-id><journal-title-group><journal-title xml:lang="ru">Russian Technological Journal</journal-title><trans-title-group xml:lang="en"><trans-title>Russian Technological Journal</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2782-3210</issn><issn pub-type="epub">2500-316X</issn><publisher><publisher-name>RTU MIREA</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.32362/2500-316X-2021-9-3-88-97</article-id><article-id custom-type="elpub" pub-id-type="custom">mireabulletin-331</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>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>MATHEMATICAL MODELING</subject></subj-group></article-categories><title-group><article-title>Достаточная статистика для параметра распределения Парето</article-title><trans-title-group xml:lang="en"><trans-title>Sufficient statistics for the Pareto distribution parameter</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>Пулькин</surname><given-names>И. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Pulkin</surname><given-names>I. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Пулькин Игорь Сергеевич, к.ф.-м.н., доцент кафедры высшей математики Института кибернетики</p><p>119454, Москва, пр-т Вернадского, д. 78 </p></bio><bio xml:lang="en"><p>Igor S. Pulkin, Cand. Sci. (Phys.–Math.), Associate Professor, Higher Mathematics Department, Institute of Cybernetics</p><p>78, Vernadskogo pr., Moscow, 119454 </p></bio><email xlink:type="simple">pulkin@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Татаринцев</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Tatarintsev</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Татаринцев Андрей Владимирович, к.ф.-м.н., доцент кафедры высшей математики-2 Физико-технологического института </p><p>Scopus Autor ID: 57221996001, 7004076246</p><p>119454, Москва, пр-т Вернадского, д. 78</p></bio><bio xml:lang="en"><p>Andrey V. Tatarintsev, Cand. Sci. (Phys.–Math.), Associate Professor, Department of Mathematics, Institute of Physics and Technology</p><p>Scopus Autor ID: 57221996001, 7004076246 </p><p>78, Vernadskogo pr., Moscow, 119454</p></bio><email xlink:type="simple">tatarintsev@mirea.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>МИРЭА – Российский технологический университет</institution><country>Россия</country></aff><aff xml:lang="en"><institution>MIREA – Russian Technological University</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>28</day><month>06</month><year>2021</year></pub-date><volume>9</volume><issue>3</issue><fpage>88</fpage><lpage>97</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Пулькин И.С., Татаринцев А.В., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Пулькин И.С., Татаринцев А.В.</copyright-holder><copyright-holder xml:lang="en">Pulkin I.S., Tatarintsev A.V.</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://www.rtj-mirea.ru/jour/article/view/331">https://www.rtj-mirea.ru/jour/article/view/331</self-uri><abstract><p>Актуальной является задача оценки параметров распределения Парето, в первую очередь, показателя этого распределения, по заданной выборке. В настоящей статье устанавливается, что для этой оценки достаточно знать значение произведения элементов выборки. Доказано, что это произведение является достаточной статистикой для показателя распределения Парето. На основании метода максимального правдоподобия вычислена оценка показателя степени распределения. Доказано, что эта оценка – смещенная, и обоснована формула, устраняющая смещение. Для произведения элементов выборки, рассматриваемого как случайная величина, найдены функция распределения, плотность вероятности, вычислены математическое ожидание, старшие моменты и дифференциальная энтропия. Построены соответствующие графики. Кроме того, отмечается, что достаточной статистикой является любая функция от этого произведения, в частности, среднее геометрическое. Для среднего геометрического, также рассматриваемого как случайная величина, найдены функция распределения, плотность вероятностей, также вычислены математическое ожидание, старшие моменты и дифференциальная энтропия и построены соответствующие графики. Кроме того, обосновано то, что среднее геометрическое выборки является более удобной достаточной статистикой с практической точки зрения, чем произведение элементов выборки. Также, на основании теоремы Рао – Блекуэлла – Колмогорова построены эффективные оценки параметра распределения Парето. В заключение в качестве примера развитая здесь техника применена к показательному распределению. Для него показано, что в качестве достаточной статистики для оценки неизвестного параметра этого распределения могут быть использованы как сумма, так и среднее арифметическое выборки.</p></abstract><trans-abstract xml:lang="en"><p>The task of estimating the parameters of the Pareto distribution, first of all, of an indicator of this distribution for a given sample, is relevant. This article establishes that for this estimate, it is sufficient to know the product of the sample elements. It is proved that this product is a sufficient statistic for the Pareto distribution parameter. On the basis of the maximum likelihood method the distribution degree indicator is estimated. It is proved that this estimate is biased, and a formula eliminating the bias is justified. For the product of the sample elements considered as a random variable the distribution function and probability density are found; mathematical expectation, higher moments, and differential entropy are calculated. The corresponding graphs are built. In addition, it is noted that any function of this product is a sufficient statistic, in particular, the geometric mean. For the geometric mean also considered as a random variable, the distribution function, probability density, and the mathematical expectation are found; the higher moments, and the differential entropy are also calculated, and the corresponding graphs are plotted. In addition, it is proved that the geometric mean of the sample is a more convenient sufficient statistic from a practical point of view than the product of the sample elements. Also, on the basis of the Rao–Blackwell–Kolmogorov theorem, effective estimates of the Pareto distribution parameter are constructed. In conclusion, as an example, the technique developed here is applied to the exponential distribution. In this case, both the sum and the arithmetic mean of the sample can be used as sufficient statistics.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>распределение Парето</kwd><kwd>достаточная статистика</kwd><kwd>эффективная оценка</kwd><kwd>функция распределения</kwd><kwd>моменты</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Pareto distribution</kwd><kwd>sufficient statistics</kwd><kwd>effective estimation</kwd><kwd>distribution function</kwd><kwd>moments</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">Пулькин И.С., Татаринцев А.В. Свойства оценки максимального правдоподобия показателя распределения Парето. Российский технологический журнал. 2018;6(6):77−83. https://doi.org/10.32362/2500-316X-2018-6-6-74-83</mixed-citation><mixed-citation xml:lang="en">Pulkin I.S., Tatarintsev A.V. 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