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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
Tytuł:
THE ANALYSIS OF CHANCES OF YOUNG AND MIDDLE-AGED PEOPLE FOR HAVING A JOB USING BAYESIAN LOGISTIC REGRESSION MODEL
Autorzy:
Grzenda, Wioletta
Powiązania:
https://bibliotekanauki.pl/articles/453708.pdf
Data publikacji:
2017
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:
employment
logistic regression
Bayesian inference
MCMC
Opis:
The aim of this article is to analyze the chances of having a job using Bayesian logistic regression model. In this study both young and middle-aged people have been considered. The individual characteristics of economically active people have a significant impact on their labour market status. In this research the commonly studied set of features has been extended by adding the following characteristics: marital status, financial situation of the household, health assessment and the fact of living with parents in the case of young people. In this study, Bayesian logistic regression model has been used. The Bayesian approach enabled us to incorporate information from previous studies.
Źródło:
Metody Ilościowe w Badaniach Ekonomicznych; 2017, 18, 1; 27-37
2082-792X
Pojawia się w:
Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Mathematical Foundations of Cognitive Radios
Autorzy:
Couillet, R.
Debbah, M.
Powiązania:
https://bibliotekanauki.pl/articles/308175.pdf
Data publikacji:
2009
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
Bayesian inference
cognitive radio
maximum entropy
Opis:
Recently, much interest has been directed towards software defined radios and embedded intelligence in telecommunication devices. However, no fundamental basis for cognitive radios has ever been proposed. In this paper, we introduce a fundamental vision of cognitive radios from a physical layer viewpoint. Specifically, our motivation in this work is to embed human-like intelligence in mobile wireless devices, following the three century-old work on Bayesian probability theory, the maximum entropy principle and minimal probability update. This allows us to partially answer such questions as, what are the signal detection capabilities of a wireless device, when facing a situation in which most parameters are missing, how to react and so on. As an introductory example, we will present previous works from the same authors following the cognitive framework, and especially the multi-antenna channel modeling and signal sensing.
Źródło:
Journal of Telecommunications and Information Technology; 2009, 4; 108-117
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Bayesian model of group decision-making
Autorzy:
Wibig, T.
Karbowiak, M.
Jaszczyk, M.
Powiązania:
https://bibliotekanauki.pl/articles/406565.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
conformity
decision-making
Bayesian inference
groupthink
cooperation
Opis:
A change in the opinion of a group, treated as a network of communicating agents, caused by the accumulation of new information is expected to depend on communication within the group, cooperation and, possibly, a kind of conformity mechanism. We have developed a mathematical model of the creation of a group decision, including this effect. This is based on a Bayesian description of inference and can be used for both conscious and inattentive acts. This model can be used to study the effect of whether a leader exists or not and other group inhomogeneities, as well as establishing the (statistical) significance and quality of a group decision. The proposed evolution equations explain in a straightfor-ward, analytical way some general properties of the general phenomenon of conformity (groupthink). To illustrate this theoretical idea in practice, we created an information technology (IT) tool to study the effect of conformity in a small group. As an example, we present results of an experiment performed using a network of students’ tablets, which could not only measure group pressure, but also conduct and control collaborative thinking in the group.
Źródło:
Operations Research and Decisions; 2016, 26, 1; 95-110
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
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:
Bayesian Propositional Logic
Autorzy:
Jarmużek, Tomasz
Klonowski, Mateusz
Malinowski, Jacek
Powiązania:
https://bibliotekanauki.pl/articles/750026.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
logical entailment
statistical inference
Bayesian inference
corroboration
confirmation
Opis:
We define and investigate from a logical point of view a family of consequence relations defined in probabilistic terms. We call them relations of supporting, and write: |≈w where w is a probability function on a Boolean language. A |≈w B iff the fact that A is the case does not decrease a probability of being B the case. Finally, we examine the intersection of |≈w , for all w, and give some formal properties of it.
Źródło:
Bulletin of the Section of Logic; 2017, 46, 3/4
0138-0680
2449-836X
Pojawia się w:
Bulletin of the Section of Logic
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian Exponential Survival Model in the Analysis of Unemployment Duration Determinants
Bayesowski wykładniczy model przeżycia w analizie determinant długości czasu pozostawania bez pracy
Autorzy:
Grzenda, Wioletta
Powiązania:
https://bibliotekanauki.pl/articles/906856.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
unemployment
survival exponential model
Bayesian inference
MCMC method
Opis:
The primary objective of the work is to identify demographic and socio-economic factors influencing the unemployment duration in the recent period in Poland. Different approaches to the problem have been applied. In this paper we have used a survival parametric model in Bayesian approach. The following determinants have been concerned in the model: sex, marital status, education level, information about continuing an education, region of Poland, and age of respondent. The empirical analysis is based on “Household budgets in 2008” survey of Central Statistical Office and indicates the main factors influencing unemployment duration.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2012, 269
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
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:
Zastosowanie wnioskowania bayesowskiego w procesie diagnozowania systemów sterowania ruchem kolejowym
Application of bayesian inference in the process of diagnosing railway traffic control systems
Autorzy:
Nowakowski, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/248547.pdf
Data publikacji:
2019
Wydawca:
Stowarzyszenie Inżynierów i Techników Komunikacji Rzeczpospolitej Polskiej
Tematy:
systemy sterowania ruchem kolejowym
diagnostyka
wnioskowanie bayesowskie
railway traffic control systems
diagnostics
Bayesian inference
Opis:
Systemy sterowania ruchem kolejowym odgrywają istotne znaczenie w zapewnieniu bezpieczeństwa przemieszczania osób i przewozu ładunków. Bardzo duża ilość urządzeń i systemów sterowania ruchem kolejowym, a także fakt, że wykonane są one w różnej technologii powoduje istotne utrudnienie w zapewnieniu, przez zarządcę infrastruktury kolejowej, wymaganego poziomu niezawodności. Konieczne jest więc wspieranie procesu ich utrzymania z użyciem metod diagnostyki technicznej. Oprogramowanie diagnostyczne CUiD przeznaczone jest głównie dla rozwiązań technicznych konkretnych producentów systemów sterowania ruchem kolejowym. Dlatego też autor artykułu zaproponował uniwersalną metodę diagnostyczną wykorzystującą wnioskowanie bayesowskie. Bazując na tej metodzie oraz protokole SNMP opracowano oprogramowanie komputerowe, które następnie użyto do diagnozowania uszkodzeń systemu SSP.
Railway traffic control systems are essential to ensure the safety of passengers and freight transport. The very large number of controlling devices and systems, but also the fact that they are made in different technologies make it very difficult for the infrastructure manager to ensure the required level of reliability. Therefore, it is necessary to support the process of their maintenance with support of the application of technical diagnostic methods. The software M&DC is created mainly for technical solutions of specific manufacturers of railway traffic control systems. Therefore, the author of the article proposed a universal diagnostic method based on Bayesian inference. On the basis of this method and the SNMP protocol, computer software was developed, which is used to diagnose faults in the LCPS.
Źródło:
Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne; 2019, 2(119); 159--168
1231-9171
Pojawia się w:
Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian Pricing of an European Call Option Using a GARCH Model with Asymmetries
Bayesowska wycena europejskiej opcji kupna z wykorzystaniem modelu GARCH z asymetriami
Autorzy:
Osiewalski, Jacek
Pipień, Mateusz
Powiązania:
https://bibliotekanauki.pl/articles/906870.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Bayesian inference
financial econometrics
volatility models
forecasting
derivative pricing
Opis:
In this paper option pricing is treated as an application of Bayesian predictive analysis. The distribution of the discounted payoff, induced by the predictive density of future observables, is the basis for direct option pricing, as in Bauwens and Lubrano (1997). We also consider another, more eclectic approach to option pricing, where the predictive distribution of the Black-Scholes value is used (with volatility measured by the conditional standard deviation at time of maturity). We use a model framework that allows for two types of asymmetry in GARCH processes: skewed t conditional densities and different reactions of conditional scale to positive/negative stocks. Our skewed t-GARCH(l, 1) model is used to describe daily changes of the Warsaw Stock Exchange Index (WIG) from 4.01.1995 till 8.02.2002. The data till 28.09.2001 are used to obtain the posterior and predictive distributions, and to illustrate Bayesian option pricing for the remaining period.
W prezentowanym artykule wycena opcji jest traktowana jako jedno z zastosowań bayesowskiej analizy predyktywnej. Rozkład wartości zdyskontowanej wypłaty, indukowany przez gęstość predyktywną przyszłych stóp zwrotu, jest podstawą bezpośredniej wyceny opcji (zob. Bauwens, Lubrano, 1997). Rozważamy też bardziej eklektyczne podejście, wykorzystujące rozkład predyktywny formuły Blacka i Scholesa (ze zmiennością określoną jako warunkowe odchylenie standardowe w momencie realizacji opcji). Przyjmujemy ramy modelowe, które uwzględniają dwa rodzaje asymetrii w procesach GARCH: skośne rozkłady warunkowe (typu t-Studenta) oraz zróżnicowane reakcje wariancji warunkowej na szoki dodatnie lub ujemne. Model: skośny £-GARCH(l, 1) jest stosowany do opisu dziennej zmienności Warszawskiego Indeksu Giełdowego (WIG) od 4.01.1995 r. do 8.02.2002 r. Dane do 28.09.2001 wykorzystujemy do budowy rozkładów a posteriori i predyktywnego oraz do ilustracji bayesowskiej wyceny opcji na pozostały okres.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2004, 177
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Change-point detection in CO2 emission-energy consumption nexus using a recursive Bayesian estimation approach
Autorzy:
Awe, Olushina Olawale
Adepoju, Abosede Adedayo
Powiązania:
https://bibliotekanauki.pl/articles/1358349.pdf
Data publikacji:
2020-03-23
Wydawca:
Główny Urząd Statystyczny
Tematy:
dynamic model
Bayesian inference
CO2
climate change
energy
Opis:
This article focuses on the synthesis of conditional dependence structure of recursive Bayesian estimation of dynamic state space models with time-varying parameters using a newly modified recursive Bayesian algorithm. The results of empirical applications to climate data from Nigeria reveals that the relationship between energy consumption and carbon dioxide emission in Nigeria reached the lowest peak in the late 1980s and the highest peak in early 2000. For South Africa, the slope trajectory of the model descended to the lowest in the mid-1990s and attained the highest peak in early 2000. These changepoints can be attributed to the economic growth, regime changes, anthropogenic activities, vehicular emissions, population growth and industrial revolution in these countries. These results have implications on climate change prediction and global warming in both countries, and also shows that recursive Bayesian dynamic model with time-varying parameters is suitable for statistical inference in climate change and policy analysis.
Źródło:
Statistics in Transition new series; 2020, 21, 1; 123-136
1234-7655
Pojawia się w:
Statistics in Transition new series
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:
Sparse Bayesian learning in classifying face feature vectors
Autorzy:
Momot, A.
Kawulok, M.
Powiązania:
https://bibliotekanauki.pl/articles/333794.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
wnioskowanie bayesowskie
rozpoznanie twarzy
supervised learning
Bayesian inference
face recognition
Opis:
The Relevance Vector Machine (RVM), a Bayesian treatment of generalized linear model of identical functional form to the Support Vector Machine (SVM), is the recently developed machine learning framework capable of building simple models from large sets of candidate features. The paper describes the application of the RVM to a classification algorithm of face feature vectors, obtained by Eigenfaces method. Moreover, the results of the RVM classification are compared with those obtained by using both the Support Vector Machine method and the method based on the Euclidean distance.
Źródło:
Journal of Medical Informatics & Technologies; 2005, 9; 151-158
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On Bayesian Inference for Almost Periodic in Mean Autoregressive Models
Wnioskowanie bayesowskie dla zmiennej w czasie prawie okresowej funkcji wartości oczekiwanej w modelu autoregresji
Autorzy:
Lenart, Łukasz
Mazur, Błażej
Powiązania:
https://bibliotekanauki.pl/articles/1050550.pdf
Data publikacji:
2016-09-30
Wydawca:
Główny Urząd Statystyczny
Tematy:
Bayesian inference
almost periodic mean function
autoregressive model
MCMC sampler
wnioskowanie bayesowskie
funkcja prawie okresowa wartości oczekiwanej
model autoregresji
próbnik MCMC
Opis:
The goal of the paper is to discuss Bayesian estimation of a class of univariate time-series models being able to represent complicated patterns of “cyclical” fluctuations in mean function. We highlight problems that arise in Bayesian estimation of parametric time-series model using the Flexible Fourier Form of Gallant (1981). We demonstrate that the resulting posterior is likely to be highly multimodal, therefore standard Markov Chain Monte Carlo (MCMC in short) methods might fail to explore the whole posterior, especially when the modes are separated. We show that the multimodality is actually an issue using the exact solution (i.e. an analytical marginal posterior) in an approximate model. We address that problem using two essential steps. Firstly, we integrate the posterior with respect to amplitude parameters, which can be carried out analytically. Secondly, we propose a non-parametrically motivated proposal for the frequency parameters. This allows for construction of an improved MCMC sampler that effectively explores the space of all the model parameters, with the amplitudes sampled by the direct approach outside the MCMC chain. We illustrate the problem using simulations and demonstrate our solution using two real-data examples.
Źródło:
Przegląd Statystyczny; 2016, 63, 3; 255-272
0033-2372
Pojawia się w:
Przegląd Statystyczny
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:
The Significance of Prior Information in Bayesian Parametric Survival Models
Znaczenie informacji a priori w bayesowskich parametrycznych modelach przeżycia
Autorzy:
Grzenda, Wioletta
Powiązania:
https://bibliotekanauki.pl/articles/905774.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
survival parametric models
Bayesian inference
prior distribution
MCMC method
unemployment
Opis:
The Bayesian approach gives the possibility of using in the research additional information that is external to the sample. The primary objective of this paper is to analyse the impact of the prior information on the posterior distribution in Bayesian parametric survival models. In this work the exponential models and Weibull models with different prior distributions have been estimated and compared. The aim of this research is to investigate the determinants of unemployment duration. The models have been estimated using Markov chain Monte Carlo method with Gibbs sampling.
W pracy przedstawiono parametryczne modele przeżycia w ujęciu bayesowskim. Podejście bayesowskie wymaga zadania rozkładów a priori dla szacowanych parametrów modelu. Rozkład a priori parametru jest rozkładem prawdopodobieństwa, który wyraża całą wiedzę badacza o szacowanym parametrze przed sprawdzeniem aktualnych danych. W literaturze przedmiotu często spotyka się nieinformacyjne rozkłady a priori, które wyrażają brak wstępnej wiedzy badacza o szacowanych parametrach modelu. W celu pokazania znaczenia informacji a priori oraz jej wpływu na rozkład a posteriori oszacowano kilka parametrycznych modeli przeżycia przy różnych rozkładach a priori. Przedmiot badań stanowią determinanty długości czasu pozostawania bez pracy.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2013, 285
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-25 z 55

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