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Wyszukujesz frazę "bayesian inference" wg kryterium: Temat


Wyświetlanie 1-12 z 12
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:
Type A Standard Uncertainty of Long-Term Noise Indicators
Autorzy:
Batko, W. M.
Stępień, B.
Powiązania:
https://bibliotekanauki.pl/articles/176923.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
long-term noise indicator
uncertainty
non-classical statistics
kernel density estimation
bootstrap
Bayesian inference
Opis:
The problem of estimation of the long-term environmental noise hazard indicators and their uncer- tainty is presented in the present paper. The type A standard uncertainty is defined by the standard deviation of the mean. The rules given in the ISO/IEC Guide 98 are used in the calculations. It is usually determined by means of the classic variance estimators, under the following assumptions: the normality of measurements results, adequate sample size, lack of correlation between elements of the sample and observation equivalence. However, such assumptions in relation to the acoustic measurements are rather questionable. This is the reason why the authors indicated the necessity of implementation of non-classical statistical solutions. An estimation idea of seeking density function of long-term noise indicators distri- bution by the kernel density estimation, bootstrap method and Bayesian inference have been formulated. These methods do not generate limitations for form and properties of analyzed statistics. The theoretical basis of the proposed methods is presented in this paper as well as an example of calculation process of expected value and variance of long-term noise indicators LDEN and LN. The illustration of indicated solutions and their usefulness analysis were constant due to monitoring results of traffic noise recorded in Cracow, Poland.
Źródło:
Archives of Acoustics; 2014, 39, 1; 25-36
0137-5075
Pojawia się w:
Archives of Acoustics
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:
Transmission of Fertility Pattern in Mother-Daughter Relation – Bayesian view (a case study of Austria)
Autorzy:
Osiewalska, Beata
Powiązania:
https://bibliotekanauki.pl/articles/418297.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
fertility patterns
intergenerational transmission of fertility
Zero-Inflated Poisson
fertility modeling
Bayesian inference
fertility in Austria
Opis:
The connection between fertility of parents and their children has been investigated many times over the past century. It seems to be insignificant among pre-transitional populations, but becomes more important over time, especially in developed countries. Following Pearson’s example, it was widely adopted to use simple correlation analyses in such studies. In this study we will present how to use more advanced statistical models and methods to determine the occurrence and strength of examined relationships. Thus, we aim to investigate the intergenerational transmission of fertility in contemporary populations (in the case of the motherdaughter relation in Austria) using the zero-inflated Poisson regression model. Using this model in fertility analysis allows us to treat childlessness as a qualitatively different state with possibly different determinants than parenthood (regardless of the number of children). Bayesian inference in this study enables us to obtain covariates’ distributions as well as distributions of covariates’ nonlinear functions (including their uncertainty) and allows us to incorporate our prior knowledge.
Źródło:
Studia Demograficzne; 2013, 163, 1; 3-35
0039-3134
Pojawia się w:
Studia Demograficzne
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 1-12 z 12

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