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Wyszukujesz frazę "exact likelihood" wg kryterium: Temat

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    Wyświetlanie 1-2 z 2
    Tytuł:
    A Bayes algorithm for model compatibility and comparison of ARMA( p; q) models
    Autorzy:
    Tripathi, Praveen Kumar
    Sen, Rijji
    Upadhyay, S. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/1054568.pdf
    Data publikacji:
    2021-06-04
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    ARMA model
    exact likelihood
    Gibbs sampler
    Metropolis algorithm
    posterior predictive loss
    model compatibility
    Ljung-Box-Pierce statistic
    GDP growth rate
    Opis:
    The paper presents a Bayes analysis of an autoregressive-moving average model and its components based on exact likelihood and weak priors for the parameters where the priors are defined so that they incorporate stationarity and invertibility restrictions naturally. A Gibbs- Metropolis hybrid scheme is used to draw posterior-based inferences for the models under consideration. The compatibility of the models with the data is examined using the Ljung- Box-Pierce chi-square-based statistic. The paper also compares different compatible models through the posterior predictive loss criterion in order to recommend the most appropriate one. For a numerical illustration of the above, data on the Indian gross domestic product growth rate at constant prices are considered. Differencing the data once prior to conducting the analysis ensured their stationarity. Retrospective short-term predictions of the data are provided based on the final recommended model. The considered methodology is expected to offer an easy and precise method for economic data analysis.
    Źródło:
    Statistics in Transition new series; 2021, 22, 2; 95-123
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Methods for combining probability and nonprobability samples under unknown overlaps
    Autorzy:
    Savitsky, Terrance D.
    Williams, Matthew R.
    Gershunskaya, Julie
    Beresovsky, Vladislav
    Powiązania:
    https://bibliotekanauki.pl/articles/31342142.pdf
    Data publikacji:
    2023-12-07
    Wydawca:
    Główny Urząd Statystyczny
    Tematy:
    Survey sampling
    Nonprobability sampling
    Data combining
    Inclusion probabilities
    Exact sample likelihood
    Bayesian hierarchical modeling
    Opis:
    Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective sample size. Estimation of a population quantity derived from a convenience sample will typically result in bias since the distribution of variables of interest in the convenience sample is different from the population distribution. A recent set of approaches estimates inclusion probabilities for convenience sample units by specifying reference sample-weighted pseudo likelihoods. This paper introduces a novel approach that derives the propensity score for the observed sample as a function of inclusion probabilities for the reference and convenience samples as our main result. Our approach allows specification of a likelihood directly for the observed sample as opposed to the approximate or pseudo likelihood. We construct a Bayesian hierarchical formulation that simultaneously estimates sample propensity scores and the convenience sample inclusion probabilities. We use a Monte Carlo simulation study to compare our likelihood based results with the pseudo likelihood based approaches considered in the literature.
    Źródło:
    Statistics in Transition new series; 2023, 24, 5; 1-34
    1234-7655
    Pojawia się w:
    Statistics in Transition new series
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-2 z 2

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