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Wyszukujesz frazę "bayesian inference" wg kryterium: Temat

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    Wyświetlanie 1-10 z 10
    Tytuł:
    A Note on Lenk’s Correction of the Harmonic Mean Estimator
    Autorzy:
    Pajor, Anna
    Osiewalski, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/483355.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian inference
    marginal data density
    MCMC methods
    Opis:
    The paper refines Lenk’s concept of improving the performance of the computed harmonic mean estimator (HME) in three directions. First, the adjusted HME is derived from an exact analytical identity. Second, Lenk’s assumption concerning the appropriate subset A of the parameter space is significantly weakened. Third, it is shown that, under certain restrictions imposed on A, a fundamental identity underlying the HME also holds for improper prior densities, which substantially extends applicability of the adjusted HME.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2013, 5, 4; 271-275
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Note on Compatible Prior Distributions in Univariate Finite Mixture and Markov-Switching Models
    Autorzy:
    Kwiatkowski, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2076512.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian inference
    prior coherence
    prior compatibility
    exponential family
    Opis:
    Finite mixture and Markov-switching models generalize and, therefore, nest specifications featuring only one component. While specifying priors in the general (mixture) model and its special (single-component) case, it may be desirable to ensure that the prior assumptions introduced into both structures are compatible in the sense that the prior distribution in the nested model amounts to the conditional prior in the mixture model under relevant parametric restriction. The study provides the rudiments of setting compatible priors in Bayesian univariate finite mixture and Markov-switching models. Once some primary results are delivered, we derive specific conditions for compatibility in the case of three types of continuous priors commonly engaged in Bayesian modeling: the normal, inverse gamma, and gamma distributions. Further, we study the consequences of introducing additional constraints into the mixture model’s prior on the conditions. Finally, the methodology is illustrated through a discussion of setting compatible priors for Markov-switching AR(2) models.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2015, 4; 219-247
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian Variations on the Frisch and Waugh Theme
    Autorzy:
    Osiewalski, Jacek
    Powiązania:
    https://bibliotekanauki.pl/articles/483315.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Bayesian inference
    regression models
    SURE models
    VAR processes
    data transformations
    Opis:
    The paper is devoted to discussing consequences of the so-called Frisch-Waugh Theorem to posterior inference and Bayesian model comparison. We adopt a generalised normal linear regression framework and weaken its assumptions in order to cover non-normal, jointly elliptical sampling distributions, autoregressive specifications, additional nuisance parameters and multi-equation SURE or VAR models. The main result is that inference based on the original full Bayesian model can be obtained using transformed data and reduced parameter spaces, provided the prior density for scale or precision parameters is appropriately modified.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2011, 3, 1; 39-47
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian Stochastic Frontier Analysis of Economic Growth and Productivity Change in the EU, USA, Japan and Switzerland
    Autorzy:
    Makieła, Kamil
    Powiązania:
    https://bibliotekanauki.pl/articles/2076602.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    stochastic frontier analysis
    Bayesian inference
    productivity analysis
    economic growth decomposition
    Opis:
    The paper discusses Bayesian productivity analysis of 27 EU Member States, USA, Japan and Switzerland. Bayesian Stochastic Frontier Analysis and a twostage structural decomposition of output growth are used to trace sources of output growth. This allows us to separate the impacts of capital accumulation, labour growth, technical progress and technical efficiency change on economic development. Since estimates of the growth components are conditioned upon model parameterisation and the underlying assumptions, a number of possible specifications are considered. The best model for decomposing output growth is chosen based on the highest marginal data density, which is calculated using adjusted harmonic mean estimator
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2014, 3; 193-216
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process
    Autorzy:
    Mazur, Błażej
    Pipień, Mateusz
    Powiązania:
    https://bibliotekanauki.pl/articles/483329.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    GARCH models
    Bayesian inference
    periodically correlated stochastic processes
    volatility
    unconditional variance
    Opis:
    We discuss the empirical importance of long term cyclical effects in the volatility of financial returns. Following Amado and Terasvirta (2009), Cizek and Spokoiny (2009) and others, we consider a general conditionally heteroscedastic process with stationarity property distorted by a deterministic function that governs the possible time variability of the unconditional variance. The function proposed in this paper can be interpreted as a finite Fourier approximation of an Almost Periodic (AP) function as defined by Corduneanu (1989). The resulting model has a particular form of a GARCH process with time varying parameters, intensively discussed in the recent literature. In the empirical analyses we apply a generalisation of the Bayesian AR(1)-GARCH model for daily returns of S&P500, covering the period of sixty years of US postwar economy, including the recently observed global financial crisis. The results of a formal Bayesian model comparison clearly indicate the existence of significant long term cyclical patterns in volatility with a strongly supported periodic component corresponding to a 14 year cycle. Our main results are invariant with respect to the changes of the conditional distribution from Normal to Student-t and to the changes of the volatility equation from regular GARCH to the Asymmetric GARCH.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2012, 4, 2; 95-116
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Bayesian Approach to Matrix Balancing: Transformation of Industry-Level Data under NACE Revision
    Autorzy:
    Boratyński, Jakub
    Powiązania:
    https://bibliotekanauki.pl/articles/2076451.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    matrix balancing
    Bayesian inference
    NACE revision
    transformation matrix
    multi-sector modelling
    Opis:
    We apply Bayesian inference to estimate transformation matrix that converts vector of industry outputs from NACE Rev. 1.1 to NACE Rev. 2 classification. In formal terms, the studied issue is a representative of the class of matrix balancing (updating, disaggregation) problems, often arising in the field of multi- sector economic modelling. These problems are characterised by availability of only partial, limited data and a strong role for prior assumptions, and are typically solved using bi-proportional balancing or cross-entropy minimisation methods. Building on Bayesian highest posterior density formulation for a similarly structured case, we extend the model with specification of prior information based on Dirichlet distribution, as well as employ MCMC sampling. The model features a specific likelihood, representing accounting restrictions in the form of an underdetermined system of equations. The primary contribution, compared to the alternative, widespread approaches, is in providing a clear account of uncertainty.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2016, 4; 219-239
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The UHF-GARCH-Type Model in the Analysis of Intraday Volatility and Price Durations – the Bayesian Approach
    Autorzy:
    Huptas, Roman
    Powiązania:
    https://bibliotekanauki.pl/articles/2076507.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    intraday volatility
    price duration
    ACD model
    UHF-GARCH-type model
    Bayesian inference
    Opis:
    In empirical research on financial market microstructure and in testing some predictions from the market microstructure literature, the behavior of some characteristics of trading process can be very important and useful. Among all characteristics associated with tick-by-tick data, the trading time and the price seem the most important. The very first joint model for prices and durations, the so-called UHF-GARCH, has been introduced by Engle (2000). The main aim of this paper is to propose a simple, novel extension of Engle’s specification based on trade-to-trade data and to develop and apply the Bayesian approach to estimation of this model. The intraday dynamics of the return volatility is modelled by an EGARCH-type specification adapted to irregularly time-spaced data. In the analysis of price durations, the Box-Cox ACD model with the generalized gamma distribution for the error term is considered. To the best of our knowledge, the UHF-GARCH model with such a combination of the EGARCH and the Box-Cox ACD structures has not been studied in the literature so far. To estimate the model, the Bayesian approach is adopted. Finally, the methodology developed in the paper is employed to analyze transaction data from the Polish Stock Market.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2016, 1; 1-20
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian Estimation and Prediction for ACD Models in the Analysis of Trade Durations from the Polish Stock Market
    Autorzy:
    Huptas, Roman
    Powiązania:
    https://bibliotekanauki.pl/articles/2076574.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    autoregressive conditional duration model (ACD model)
    tradedurations
    financial market microstructure
    Bayesian inference
    Opis:
    In recent years, autoregressive conditional duration models (ACD models) introduced by Engle and Russell in 1998 have become very popular in modelling of the durations between selected events of the transaction process (trade durations or price durations) and modelling of financial market microstructure effects. The aim of the paper is to develop Bayesian inference for the ACD models. Different specifications of ACD models will be considered and compared with particular emphasis on the linear ACD model, Box-Cox ACD model, augmented Box-Cox ACD model and augmented (Hentschel) ACD model. The analysis will consider models with the Burr distribution and the generalized Gamma distribution for the innovation term. Bayesian inference will be presented and practically used in estimation of and prediction within ACD models describing trade durations. The MCMC methods including MetropolisHastings algorithm are suitably adopted to obtain samples from the posterior densities of interest. The empirical part of the work includes modelling of trade durations of selected equities from the Polish stock market.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2014, 4; 237-273
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian Inference for a Deterministic Cycle with Time-Varying Amplitude: The Case of the Growth Cycle in European Countries
    Autorzy:
    Lenart, Łukasz
    Powiązania:
    https://bibliotekanauki.pl/articles/2076240.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    deterministic cycle with time-varying amplitude
    Bayesian inference
    almost periodic function
    growth cycle
    industrial production
    Opis:
    The main goal of this paper is to propose the probabilistic description of cyclical (business) fluctuations. We generalize a fixed deterministic cycle model by incorporating the time-varying amplitude. More specifically, we assume that the mean function of cyclical fluctuations depends on unknown frequencies (related to the lengths of the cyclical fluctuations) in a similar way to the almost periodic mean function in a fixed deterministic cycle, while the assumption concerning constant amplitude is relaxed. We assume that the amplitude associated with a given frequency is time-varying and is a spline function. Finally, using a Bayesian approach and under standard prior assumptions, we obtain the explicit marginal posterior distribution for the vector of frequency parameters. In our empirical analysis, we consider the monthly industrial production in most European countries. Based on the highest marginal data density value, we choose the best model to describe the considered growth cycle. In most cases, data support the model with a time-varying amplitude. In addition, the expectation of the posterior distribution of the deterministic cycle for the considered growth cycles has similar dynamics to cycles extracted by standard bandpass filtration methods.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2018, 3; 233-262
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bayesian Inference and Gibbs Sampling in Generalized True Random-Effects Models
    Autorzy:
    Makieła, Kamil
    Powiązania:
    https://bibliotekanauki.pl/articles/2076439.pdf
    Data publikacji:
    2017
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    generalized true random-effects model
    stochastic frontier analysis
    Gibbs sampling
    Bayesian inference
    cost efficiency
    transient and persistentefficiency
    Opis:
    The paper investigates Bayesian approach to estimate generalized true random-effects models (GTRE). The analysis shows that under suitably defined priors for transient and persistent inefficiency terms the posterior characteristics of such models are well approximated using simple Gibbs sampling. No model re-parameterization is required. The proposed modification not only allows us to make more reasonable (less informative) assumptions as regards prior transient and persistent inefficiency distribution but also appears to be more reliable in handling especially noisy datasets. Empirical application furthers the research into stochastic frontier analysis using GTRE models by examining the relationship between inefficiency terms in GTRE, true random-effects, generalized stochastic frontier and a standard stochastic frontier model.
    Źródło:
    Central European Journal of Economic Modelling and Econometrics; 2017, 1; 69-95
    2080-0886
    2080-119X
    Pojawia się w:
    Central European Journal of Economic Modelling and Econometrics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-10 z 10

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