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Wyszukujesz frazę "Bayes statistics" wg kryterium: Temat

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    Wyświetlanie 1-4 z 4
    Tytuł:
    Service quality management in multipath access solutions for transport telematics solution
    Autorzy:
    Zelinka, T.
    Svítek, M.
    Starek, T.
    Lokaj, Z.
    Powiązania:
    https://bibliotekanauki.pl/articles/393293.pdf
    Data publikacji:
    2010
    Wydawca:
    Polskie Stowarzyszenie Telematyki Transportu
    Tematy:
    inteligentne systemy transportowe
    ITS
    telematyka transportu
    funkcja gęstości Laplace'a
    statystyka Bayes'a
    intelligent transport system (ITS)
    transport telematics
    Laplace density function
    Bayes statistics
    Opis:
    ITSs (Intelligent Transport systems) are associated with serious expectations and getting ITS applications in the real practice is understood as essential potential to significantly faster resolve many transport challenges. Research is concentrated on the promotion of ITS architecture in real ITS practice and using it for solving the different ITS optimization tasks. In this paper main afford is oriented to the communications key support of the ITS architecture
    Źródło:
    Archives of Transport System Telematics; 2010, 3, 4; 53-58
    1899-8208
    Pojawia się w:
    Archives of Transport System Telematics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development of Small Area Estimationin Official Statistics
    Autorzy:
    Kordos, Jan
    Powiązania:
    https://bibliotekanauki.pl/articles/466085.pdf
    Data publikacji:
    2016
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    small area estimation
    official statistics
    sampling survey
    direct estimation
    indirect estimation
    empirical Bayes estimator
    hierarchical Bayes estimator
    data quality
    Opis:
    The author begins with a general assessment of the mission of the National Statistics Institutes (NSIs), main producers of official statistics, which are obliged to deliver high quality statistical information on the state and evolution of the population, the economy, the society and the environment. These statistical results must be based on scientific principles and methods. They must be made available to the public, politics, economy and research for decision-making and information purposes. Next, before discussing general issues of small area estimation (SAE) in official statistics, the author reminds: the methods of sampling surveys, data collection, estimation procedures, and data quality assessment used for official statistics. Statistical information is published in different breakdowns with stable or even decreasing budget while being legally bound to control the response burden. Special attention is paid, from a practitioner point of view, to synthetic development of small area estimation in official statistics, beginning with international seminars and conferences devoted to SAE procedures and methods (starting with the Canadian symposium, 1985, and the Warsaw conference, 1992, to the Poznan conference, Poland, 2014), and some international projects (EURAREA, SAMPLE, BIAS, AMELI, ESSnet). Next, some aspects of development of SAE in official statistics are discussed. At the end some conclusions regarding quality of SAE procedures are considered.
    Źródło:
    Statistics in Transition new series; 2016, 17, 1; 105-132
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Decision-making under risk and “statistical thinking” in the 20th century (selected models and persons)
    Autorzy:
    Rybicki, Wojciech
    Powiązania:
    https://bibliotekanauki.pl/articles/584930.pdf
    Data publikacji:
    2018
    Wydawca:
    Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
    Tematy:
    statistics
    risk
    subjective probability
    objective probability
    frequentists
    sequential analysis
    stochastic approximation
    stochastic game
    empirical Bayes approach
    Opis:
    The paper is the second part of the series of articles surveying chosen models of decision-making under “risky circumstances”. The first segment concerned the earlier period of development of so-called “statistical thinking” (up to the times of J. Neyman and E. Pearson) and has been published elsewhere. These “twins” of papers as a whole, are intended as essays (consciously avoiding any formalization) to introduce the subsequent parts of the cycle – conducted in a more formal style. Several problems were discussed in the first part of the series. The leitmotifs, i.e. Bayesian vs. “orthodox” approaches, and the subjective vs. objective probability meaning are continued in this article, and developed towards the “modern needs and directions”. The role of some outstanding scientists is stressed. The possibility of the unification of the different philosophies on the grounds of statistical decision theory (thanks to A. Wald and L.J. Savage) is noted. “Dynamic” or multistage statistical decision procedures will be also indicated (in contrast to “static, “one-shot” problems). The primary role in developing these ideas played by mathematicians A. Wald, L. Shapley, R. Bellman, D. Blackwell and H. Robbins (plus many others) is stressed. The outline is conducted in a “historical perspective” beginning with F. Ramsey’s work and finishing at H. Robbins achievements – as being very influential in the further development of the stochastic methodology. The list of models, to be discussed in the subsequent (“formal-mode”) article/s, is added at the end of the paper. The central role in the notes is played by the “procession” of the prominent representatives of the field. The first “series” of them was presented in the previous part of the cycle. The subsequent (nine) are placed here. These scientists built the milestones of statistical science, “created its spirit,” exquisitely embedding the subject in the “general stochastic world”. The presentation is supplemented with their portraits. The author hopes that some keystones determining the line-up can be recognized in the course of reading. It is not possible to talk about mathematics without mathematics (formulas, calculations, formal reasoning). On the other hand − such beings as probability, uncertainty, risk can be, first of all, regarded as philosophic and logic in their heart of hearts (as well as being somewhat “mysterious”). So, it can turn out illuminating (sometimes) to reveal and to show merely the ideas and “their” heroes (even at the expense of losing the precision!). The role of the bibliography should also be stressed – it is purposely made so large, and significantly completes the presentation.
    Źródło:
    Mathematical Economics; 2018, 14(21); 71-94
    1733-9707
    Pojawia się w:
    Mathematical Economics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesowski model wzrostu niezawodności oparty na dynamicznych parametrach rozkładu
    Bayesian reliability growth model based on dynamic distribution parameters
    Autorzy:
    Tao, Y.
    Zhang, Y. A.
    Chen, X.
    Ming, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/301037.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
    Tematy:
    statystyka populacji niejednorodnej
    model monotoniczny
    Bayes
    model przyrostu niezawodności
    rozkład wykładniczy
    non-homo geneous population statistics
    monotone model
    reliability growth model
    exponential distribution
    Opis:
    W artykule przestudiowano metody analizy statystycznej na różnych etapach wzrostu niezawodności w oparciu o model monotoniczny. Zamodelowano zmiany jakim dynamiczne parametry rozkładu podlegają podczas badań. Podano bayesowskie modele wzrostu niezawodności dla licznych etapów wzrostu niezawodności. Na koniec metodę zweryfikowano w oparciu o przykład praktyczny.
    In this paper we study the statistical analysis methods at different stages of reliability growth based on the monotone model. The changes of dynamic distribution parameters during test are modeled. Bayesian reliability growth models for multiple stages of reliability growth are given. Finally the method is validated by a practical example.
    Źródło:
    Eksploatacja i Niezawodność; 2010, 2; 13-16
    1507-2711
    Pojawia się w:
    Eksploatacja i Niezawodność
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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