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| Nsiri, Benayad; Chonavel, Thierry; Boucher, Jean; Nouze, Herve. |
| In seismic deconvolution, blind approaches must be considered in situations where reflectivity sequence, source wavelet signal, and noise power level are unknown. In the presence of long source wavelets, strong interference among the reflectors contributions makes the wavelet estimation and deconvolution more complicated. In this paper, we solve this problem in a two-step approach. First, we estimate a moving average (MA) truncated version of the wavelet by means of a stochastic expectation-maximization (SEM) algorithm. Then, we use Prony's method to improve the wavelet estimation accuracy by fitting an autoregressive moving average (ARMA) model with the initial truncated wavelet. Moreover, a solution to the wavelet initialization problem in the SEM... |
| Tipo: Text |
Palavras-chave: Bernoulli Gaussian BG process; Blind deconvolution; Gibbs sampler; Maximum likelihood ML; Maximum posterior mode MPM; Monte Carlo Markov chains MCMCs methods; Prony algorithm; Seismic deconvolution; Stochastic expectation maximization SEM. |
| Ano: 2007 |
URL: http://archimer.ifremer.fr/doc/00000/11030/8978.pdf |
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| Frank, Julieta; Garcia, Philip. |
| Estimation of liquidity costs in agricultural futures markets is challenging because bid-ask spreads are usually not observed. Spread estimators that use transaction data are available, but little agreement exists on their relative accuracy and performance. We evaluate four conventional and a recently proposed Bayesian estimators using simulated data based on Roll’s standard liquidity cost model. The Bayesian estimator tracks Roll’s model relatively well except when the level of noise in the market is large. We derive an improved estimator that seems to have a higher performance even under high levels of noise which is common in agricultural futures markets. We also compute liquidity costs using data for hogs and cattle futures contracts trading on the... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: Liquidity costs; Bid-ask spread; Bayesian estimation; Gibbs sampler. |
| Ano: 2007 |
URL: http://purl.umn.edu/37572 |
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| Malhado,Carlos Henrique Mendes; Malhado,Ana Claudia Mendes; Ramos,Alcides de Amorim; Carneiro,Paulo Luiz Souza; Souza,Julio César de; Pala,Akin. |
| The major objective of this study was to estimate heritability and genetic correlations between milk yield (MY) and calving interval (CI) and lactation length (LL) in Murrah buffaloes using Bayesian inference. The database used belongs to the genetic improvement program of four buffalo herds from Brazil. To obtain the estimates of variance and covariance, bivariate analyses were performed with the Gibbs sampler, using the program MTGSAM. The heritability coefficient estimates were 0.28, 0.03 and 0.15 for MY, CI and LL, respectively. The genetic correlations between MY and LL was moderate (0.48). However, the genetic correlation between MY and CI showed large HPD regions (highest posterior density interval). Milk yield was the only trait with clear... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Genetic correlation; Gibbs sampler; Heritability. |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982013000800005 |
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