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Tytuł:
Stability and conditional Γ-minimaxity in Bayesian inference
Autorzy:
Męczarski, Marek
Powiązania:
https://bibliotekanauki.pl/articles/1340709.pdf
Data publikacji:
1993
Wydawca:
Polska Akademia Nauk. Instytut Matematyczny PAN
Tematy:
conditional Γ-minimax action
stability of a statistical procedure
robust Bayesian analysis
Opis:
Two concepts of optimality corresponding to Bayesian robust analysis are considered: conditional Γ-minimaxity and stability. Conditions for coincidence of optimal decisions of both kinds are stated.
Źródło:
Applicationes Mathematicae; 1993-1995, 22, 1; 117-122
1233-7234
Pojawia się w:
Applicationes Mathematicae
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian Inference for State Space Model with Panel Data
Autorzy:
Pandey, Ranjita
Chaturvedi, Anoop
Powiązania:
https://bibliotekanauki.pl/articles/466044.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
Bayesian analysis
Gibbs sampler
conditional posterior densities
predictive distribution
Opis:
The present work explores panel data set-up in a Bayesian state space model. The conditional posterior densities of parameters are utilized to determine the marginal posterior densities using the Gibbs sampler. An efficient one step ahead predictive density mechanism is developed to further the state of art in prediction-based decision making.
Źródło:
Statistics in Transition new series; 2016, 17, 2; 211-220
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wide estimation of dynamic properties of viscoelastic materials using Bayesian inference
Autorzy:
Balbino, Fernanda Oliveira
Préve, Cíntia Teixeira
Munaro, Marilda
Ribeiro Junior, Paulo Justiniano
de Oliveira Lopes, Eduardo Márcio
Powiązania:
https://bibliotekanauki.pl/articles/1839671.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
Bayesian inference
dynamic properties
posterior distribution
vibration control
viscoelastic material
Opis:
The dynamic behavior of a typical viscoelastic material in wide ranges of frequency and tem- perature is characterized. A four-parameter fractional derivative model was considered in the frequency domain along with the Arrhenius and WLF models, also for including tempera- ture as a source of variation. A Bayesian framework is adopted and inferences on parameters governing the model quantities of interest are based on samples from posterior distributions obtained by Monte Carlo Markov Chain (MCMC) methods. Posterior predictive checks were conducted to ensure the goodness-of-fit of the model. Based on the results we argue that the Bayesian framework allows more complete and suitable inference about dynamic properties of typical viscoelastic materials, as required for broad and sound vibration control actions.
Źródło:
Journal of Theoretical and Applied Mechanics; 2021, 59, 3; 369-384
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
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
Tytuł:
Missing observations in daily returns - Bayesian inference within the MSF-SBEKK model
Autorzy:
Osiewalski, Krzysztof
Osiewalski, Jacek
Powiązania:
https://bibliotekanauki.pl/articles/483257.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Bayesian econometrics
hybrid MGARCH-MSV processes
forecasting unavailable data
financial markets
commodity markets
Opis:
Often daily prices on different markets are not all observable. The question is whether we should exclude from modelling the days with prices not available on all markets (thus loosing some information and implicitly modifying the time axis) or somehow complete the missing (non-existing) prices. In order to compare the effects of each of two ways of dealing with partly available data, one should consider formal procedures of replacing the unavailable prices by their appropriate predictions. We propose a fully Bayesian approach, which amounts to obtaining the marginal posterior (or predictive) distribution for any particular day in question. This procedure takes into account uncertainty on missing prices and can be used to check validity of informal ways of "completing" the data (e.g. linear interpolation). We use the MSF-SBEKK structure, the simplest among hybrid MSV-MGARCH models, which can parsimoniously describe volatility of a large number of prices or indices. In order to conduct Bayesian inference, the conditional posterior distributions for all unknown quantities are derived and the Gibbs sampler (with Metropolis-Hastings steps) is designed. Our approach is applied to daily prices from six different financial and commodity markets; the data cover the period from December 21, 2005 till September 30, 2011, so the time of the global financial crisis is included. We compare inferences (on individual parameters, conditional correlation coefficients and volatilities), obtained in the cases where unavailable observations are either deleted or forecasted.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2012, 4, 3; 169-197
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On the use of viscoelastic materials characterized by Bayesian inference in vibration control
Autorzy:
Préve, Cíntia Teixeira
Balbino, Fernanda Oliveira
Ribeiro Junior, Paulo Justiniano
de Oliveira Lopes, Eduardo Márcio
Powiązania:
https://bibliotekanauki.pl/articles/1839679.pdf
Data publikacji:
2021
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
viscoelastic material
Bayesian inference
vibration isolator
viscoelastic dynamic neutralizer
Opis:
Viscoelastic materials are used to reduce vibrations in mechanical systems due to their con- trol efficacy. Considering that the dynamic behavior of those materials may be described by means of complex moduli, and experimental data may present ucertainties, an alternative is to use probabilistic methods, especially the Bayesian inference approach. By that approach, probability distribution functions are obtained for parameters of a model which describes the behavior of a given material. The present work employs a viscoelastic material modeled by the Bayesian approach in two vibration control actions, namely: a) use of vibration isolators; b) use of dynamic neutralizers. Transmissibility and receptance curves are displayed as well as dimensions of the control devices. Performance predictions are carried out in both cases. It is shown that the Bayesian approach can favourably reflect the presence of the uncertain- ties and advance their effects. Thus, more information can be provided for the designer of viscoelastic vibration control devices to anticipate eventual corrective measures.
Źródło:
Journal of Theoretical and Applied Mechanics; 2021, 59, 3; 385-399
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Point Nuisance Method as a decision-support system based on bayesian inference approach
Autorzy:
Rusek, Janusz
Powiązania:
https://bibliotekanauki.pl/articles/219946.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
odporność budynku
obszar wydobycia
niezawodność
deformacja powierzchni
resistance of buildings
mining area
reliability
surface deformations
Opis:
The article attempts to transfer information from the Point Nuisance Method (PNM) used in Poland in the issue of protection of buildings in mining areas, to the system of inference based on Bayesian formalism. For this purpose, all possible combinations occurring in PNM were selected. The number of numerically generated patterns was 6,718,464 cases. Then, based on Python package Scikit-Learn, a classification model was created in the form of the Naïve Bayes Classifier (NBC). The effectiveness of three methods used to build this type of decision-support system was analysed, from which the Categorical Multinomial Naive Bayes (CMNB) approach was finally selected. With the created classifier, its properties were verified in terms of quality of classify and generalization. For this purpose a general approach was used, analysing the level of accuracy of the model in relation to training and teaching data, and detailed, based on the analysis of the confusion matrix. Additionally, the operation of the created classifier was simulated to determine the optimal Laplace smoothing parameter α. The article ends with conclusions from the carried out calculations, in which an attempt was made to answer the question concerning potential reasons for incorrect classification of the created CMNB model. The discussion ends with a reference to the planned research, in which, among other things, the use of more complex Bayesian belief networks (BBN) is planned.
Źródło:
Archives of Mining Sciences; 2020, 65, 1; 117-127
0860-7001
Pojawia się w:
Archives of Mining Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of the Bayesian Inference for Estimation of the Long-Term Noise Indicators and Their Uncertainty
Autorzy:
Batko, W.
Stępień, B.
Powiązania:
https://bibliotekanauki.pl/articles/1504185.pdf
Data publikacji:
2011-06
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
43.50.Rq
43.50.Yw
Opis:
The problem of estimation of the environmental noise hazard indicators and their uncertainty is presented in the hereby paper. The main attention is focused on the estimation process of the long-term noise indicators and their type A standard uncertainty defined by the standard deviation of the mean of the measurement results. 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, at the assumption of the normality of measurements results. However, such assumption in relation to the acoustic measurements is rather questionable. This is the reason that the authors indicated the necessity of implementation of non-classic statistic solutions. There was formulated the estimation idea of seeking density function of long-term noise indicators distribution by the Bayesian inference, which does not generate limitations for form and properties of analyzed statistics. There was presented theoretical basis of the proposed method, and the example of calculation process which make possible determining searched estimators of expected value and variance of long-term noise indicators $L_{DEN}$ and $L_{N}$. The illustration for indicated solutions and usefulness analysis was constant monitoring results of traffic noise recorded on one of the main arteries of Kraków, Poland.
Źródło:
Acta Physica Polonica A; 2011, 119, 6A; 916-920
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
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:
Infinitesimal robustness in Bayesian statistical models
Autorzy:
Boratyńska, Agata
Powiązania:
https://bibliotekanauki.pl/articles/748078.pdf
Data publikacji:
1994
Wydawca:
Polskie Towarzystwo Matematyczne
Tematy:
Bayesian inference
Robustness and adaptive procedures
Opis:
.
The problem of measuring the Bayesian robustness is considered. An upper bound for the oscillation of a posterior functional in terms of the Kolmogorov distance between the prior distributions is given. The norm of the Frechet derivative as a measure of local sensitivity is presented. The problem of finding optimal statistical procedures is presented.
Źródło:
Mathematica Applicanda; 1994, 23, 37
1730-2668
2299-4009
Pojawia się w:
Mathematica Applicanda
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-10 z 55

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