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Wyszukujesz frazę "Hierarchical Bayes" wg kryterium: Temat


Wyświetlanie 1-8 z 8
Tytuł:
Economic Analysis of Charitable Donations
Autorzy:
Young Kang, Moon
Park, Byungho
Lee, Sanghak
Kim, Jaehwan
Allenby, Greg
Powiązania:
https://bibliotekanauki.pl/articles/540580.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
Tematy:
direct utility model
hierarchical Bayes
altruism
non-profit marketing
Opis:
This paper examines the effect of message characteristics on donation behavior using an economic model of giving. The utility of giving can come from one’s own contribution and possibly from the combined contributions of others. Donors are assumed to be constrained utility maximizers, and the message attributes affect the degree to which they react altruistically or egoistically. The model is estimated with data from an incentive-aligned study of South Korean consumers, and implications for message optimization and donor targeting are explored.
Źródło:
Journal of Marketing and Consumer Behaviour in Emerging Markets; 2016, 2(4); 40-57
2449-6634
Pojawia się w:
Journal of Marketing and Consumer Behaviour in Emerging Markets
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bayesian approach to shipping reliability and safety
Autorzy:
Smolarek, L.
Powiązania:
https://bibliotekanauki.pl/articles/2069249.pdf
Data publikacji:
2012
Wydawca:
Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:
reliability
safety
shipping
hierarchical Bayes model
prior model
Opis:
In a Bayesian approach, there are two main sources of information about parameters of interest such as prior beliefs or the prior distribution of the parameter and the likelihood of observing the data given our expectations about the parameter. The prior distribution may be based on previous studies, literature reviews or expert opinions and indicates how we believe the parameter would behave if we had no data upon which to base our judgments. In case where we have less data, the prior has greater influence. The maximum likelihood estimate predominates only when we have a lot of data. The posterior distribution is the result of combining the prior distribution and the likelihood. In the paper the examples of using Bayes approach to shipping operational reliability and safety is presented.
Źródło:
Journal of Polish Safety and Reliability Association; 2012, 3, 2; 227--236
2084-5316
Pojawia się w:
Journal of Polish Safety and Reliability Association
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of bayesian estimation methods for small domains in the Polish Labor Force Survey
Zastosowanie bayesowskich metod estymacji dla małych obszarów w Badaniu Aktywności Ekonomicznej Ludności
Autorzy:
Kubacki, Jan
Powiązania:
https://bibliotekanauki.pl/articles/906830.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
small area estimation
labor force survey
model approach
empirical Bayes estimation
hierarchical Bayes estimation
Opis:
The author presents a synthetic overview of recent efforts related to the small area estimation methods applied to the Polish Labor Force Survey (PLFS). The review concerns methodology and results obtained by Central Statistical Office connected with PLFS and National Census and some results obtained by the author of this paper. In the paper author discusses various methods of estimation together with evaluation of quality of such estimation. In particular the relationship between quality of Bayes estimates type and quality of a priori estimates and also type of applied method of estimation is presented.
Referat przedstawia syntetyczny przegląd przeprowadzonych ostatnio badań, dotyczących zastosowania metod statystyki małych obszarów, z użyciem wyników z Badania Aktywności Ekonomicznej Ludności. Przegląd dotyczy zagadnień metodologicznych oraz wyników otrzymanych przez Główny Urząd Statystyczny, związanych z BAEL oraz Spisem Powszechnym 2002, jak również wynikami otrzymanymi przez autora niniejszego referatu. W referacie dyskutowane są różne metody estymacji, łącznie z szacunkami ich jakości. W szczególności przedstawione została zależność jakości danych szacowanych z użyciem metod bayesowskich od jakości szacunków a priori oraz rodzaju zastosowanej metody estymacji.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2008, 216
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Estimation of Parameters for Small Areas Using Hierarchical Bayes Method in the Case of Known Model Hyperparameters
Autorzy:
Kubacki, Jan
Powiązania:
https://bibliotekanauki.pl/articles/465703.pdf
Data publikacji:
2012
Wydawca:
Główny Urząd Statystyczny
Tematy:
Small area estimation
hierarchical Bayes estimation WinBUGS
Opis:
In the paper the method of parameters estimation using hierarchical Bayes (HB) method in the case of known model hyperparameters for a priori conditionals was presented. This approach has some advantage in comparison with subjective model parameters selection because of more simulation stability and allows obtaining estimates that has more regular distribution. As an example the data about average per capita income from Polish Household Budget Survey for counties (NUTS4) and auxiliary variables from Polish Tax Register (POLTAX) were used. The computation was done using WinBUGS software and R-project environment with R2WinBUGS package, which control the simulations in WinBUGS, and coda package, which allows performing the analysis of simulation results. In the paper sample code in R-project that can be used as a pattern for further similar applications was also presented. The efficiency of hierarchical Bayes estimation with other small area methods was compared. Such comparison was done for HB and EBLUP techniques, for which some consistency related to the precision of estimates obtained using both techniques was achieved.
Źródło:
Statistics in Transition new series; 2012, 13, 2; 261-278
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Small Area Estimation of Income Under Spatial SAR Model
Autorzy:
Kubacki, Jan
Jędrzejczak, Alina
Powiązania:
https://bibliotekanauki.pl/articles/465667.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
small area estimation (SAE)
SAR model
hierarchical Bayes estimation
spatial empirical best linear unbiased predictor
Opis:
The paper presents the method of hierarchical Bayes (HB) estimation under small area models with spatially correlated random effects and a spatial structure implied by the Simultaneous Autoregressive (SAR) process. The idea was to improve the spatial EBLUP by incorporating the HB approach into the estimation algorithm. The computation procedure applied in the paper uses the concept of sampling from a posterior distribution under generalized linear mixed models implemented in WinBUGS software and adapts the idea of parameter estimation for small areas by means of the HB method in the case of known model hyperparameters. The illustration of the approach mentioned above was based on a real-world example concerning household income data. The precision of the direct estimators was determined using own three-stage procedure which employs Balanced Repeated Replication, bootstrap and Generalized Variance Function. Additional simulations were conducted to show the influence of the spatial autoregression coefficient on the estimation error reduction. The computations performed by ‘sae’ package for R project and a special procedure for WinBUGS reveal that the method provides reliable estimates of small area means. For high spatial correlation between domains, noticeable MSE reduction was observed, which seems more evident for HB-SAR method as compared with the traditional spatial EBLUP. In our opinion, the Gibbs sampler, revealing the simultaneous nature of processes, especially for random effects, can be a good starting point for the simulations based on stochastic SAR processes.
Źródło:
Statistics in Transition new series; 2016, 17, 3; 365-390
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of Small Area Estimationin Official Statistics
Autorzy:
Kordos, Jan
Powiązania:
https://bibliotekanauki.pl/articles/466085.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
small area estimation
official statistics
sampling survey
direct estimation
indirect estimation
empirical Bayes estimator
hierarchical Bayes estimator
data quality
Opis:
The author begins with a general assessment of the mission of the National Statistics Institutes (NSIs), main producers of official statistics, which are obliged to deliver high quality statistical information on the state and evolution of the population, the economy, the society and the environment. These statistical results must be based on scientific principles and methods. They must be made available to the public, politics, economy and research for decision-making and information purposes. Next, before discussing general issues of small area estimation (SAE) in official statistics, the author reminds: the methods of sampling surveys, data collection, estimation procedures, and data quality assessment used for official statistics. Statistical information is published in different breakdowns with stable or even decreasing budget while being legally bound to control the response burden. Special attention is paid, from a practitioner point of view, to synthetic development of small area estimation in official statistics, beginning with international seminars and conferences devoted to SAE procedures and methods (starting with the Canadian symposium, 1985, and the Warsaw conference, 1992, to the Poznan conference, Poland, 2014), and some international projects (EURAREA, SAMPLE, BIAS, AMELI, ESSnet). Next, some aspects of development of SAE in official statistics are discussed. At the end some conclusions regarding quality of SAE procedures are considered.
Źródło:
Statistics in Transition new series; 2016, 17, 1; 105-132
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Comparison of Small Area Estimation Methods for Poverty Mapping
Autorzy:
Guadarrama, María
Molina, Isabel
Rao, J. N. K.
Powiązania:
https://bibliotekanauki.pl/articles/465671.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
area level model
non-linear parameters
empirical best estimator
hierarchical Bayes
poverty mapping
unit level models
Opis:
We review main small area estimation methods for the estimation of general nonlinear parameters focusing on FGT family of poverty indicators introduced by Foster, Greer and Thorbecke (1984). In particular, we consider direct estimation, the Fay-Herriot area level model (Fay and Herriot, 1979), the method of Elbers, Lanjouw and Lanjouw (2003) used by the World Bank, the empirical Best/Bayes (EB) method of Molina and Rao (2010) and its extension, the Census EB, and finally the hierarchical Bayes proposal of Molina, Nandram and Rao (2014). We put ourselves in the point of view of a practitioner and discuss, as objectively as possible, the benefits and drawbacks of each method, illustrating some of them through simulation studies.
Źródło:
Statistics in Transition new series; 2016, 17, 1; 41-66
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Two-Component Normal Mixture Alternative to the Fay-Herriot Model
Autorzy:
Chakraborty, Adrijo
Datta, Gauri Sankar
Mandal, Abhyuday
Powiązania:
https://bibliotekanauki.pl/articles/465632.pdf
Data publikacji:
2016
Wydawca:
Główny Urząd Statystyczny
Tematy:
Hierarchical Bayes
heavy-tail distribution
non-informative priors
robustness to outliers
small area estimation
Opis:
This article considers a robust hierarchical Bayesian approach to deal with random effects of small area means when some of these effects assume extreme values, resulting in outliers. In the presence of outliers, the standard Fay-Herriot model, used for modeling area-level data, under normality assumptions of random effects may overestimate the random effects variance, thus providing less than ideal shrinkage towards the synthetic regression predictions and inhibiting the borrowing of information. Even a small number of substantive outliers of random effects results in a large estimate of the random effects variance in the Fay-Herriot model, thereby achieving little shrinkage to the synthetic part of the model or little reduction in the posterior variance associated with the regular Bayes estimator for any of the small areas. While the scale mixture of normal distributions with a known mixing distribution for the random effects has been found to be effective in the presence of outliers, the solution depends on the mixing distribution. As a possible alternative solution to the problem, a two-component normal mixture model has been proposed, based on non-informative priors on the model variance parameters, regression coefficients and the mixing probability. Data analysis and simulation studies based on real, simulated and synthetic data show an advantage of the proposed method over the standard Bayesian Fay-Herriot solution derived under normality of random effects.
Źródło:
Statistics in Transition new series; 2016, 17, 1; 67-90
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-8 z 8

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