When image noise reduction is carried out by Bayesian estimation method, the peak SNR is improved from -12.084dB to 10.084dB, the position deviation of the centroid is only 0.03μm.

Wavelet transform is used to estimate the noise, namely is generalized Gaussian noise. For this, a noise reduction method based on Bayesian estimation is proposed.

while spatial domainalgorithms have mainly three approaches, i.e. Iterative Backward Projecting(IBP),Projection Onto Convex Sets(POCS) and Bayesian methods.

With an eye to the shortcomings of UCAT, the item selection, trait estimation are discussed in theory and the algorithm of Bayesian item selection about MAT is putted forward.

spatial domain algorithms there are mainly three approaches, i.e. Iterative Backward Projecting(IBP), Projection Onto Convex Sets(POCS) and Bayesian methods.

Consideration was given to the Bayesian estimation in the multidimensional indefinite-stochastic observation model using the minimax criterion with the generalized probabilistic risk functionals.

In the first case, nonlinear regression analysis is used in combination with successive Bayesian estimation.

The map is represented by an occupancy grid framework and updated by the Bayesian estimation mechanism.

A Bayesian estimation framework was chosen to build up a regularization scheme based on the weak membrane model.

Dynamic Bayesian estimation of displacement parameters of continuous curve box based on Novozhilov theory

The Bayesian approach is applied to this problem and, using Monte Carlo simulation to search over the integer candidates, a practical expression for the Bayesian estimator is obtained.

Subsequently, these parameters were used by the Bayesian estimator to calculate individual pharmacokinetics from only 2 or 3 measured concentrations.

The comparison of results obtained from the Bayesian estimator and from the three-compartment model showed that CL and t1/2 were well predicted (relative deviation: ±12 to 22%) by the Bayesian method using only two blood samples.

Relative estimation errors of the obtained empirical Bayesian estimator are very small - they do not exceed 2.5%.

A Bayesian estimator, based on the Gibbs sampling, is proposed.

But if the assumptions of the model are not violated, then the maximum and mean likelihood and the Bayesian estimators are best.

Pseudo Bayesian estimators for the variance components based on Jeffrey's Rule are derived for the mixed balanced incomplete block design and are compared with the usual analysis of variance estimators in terms of mean squared error (MSE) efficiency.

Numerical results show that Pseudo-Bayesian estimators are more efficient in numerical results.

The Bayesian estimators are shown to provide some improvement over lognormal co-kriging under the criteria of mean error, root mean square error, and standardized mean square error.

The proposed estimators are arguably superior to the traditional estimators and to the usual Bayesian estimators, and may be highly robust.

In this paper, we consider linear regression Y=Xβ+ε,ε～N(0,σ~2I_k) where β and σ~2 are unknown parameters. With general quadratic loss function, we first construct Bayesian estimators of the parameters of multiparameter exponential families. Using multiple kernel function, we censtruct the EB estimators of the parameters. We obtain their rases of convergence 2(σr-1)/(2r+p+1) closing to 1.

本文研究了正态线性模型回归系数与误差方差联立经验Bayesian估计的收敛速度。

Genetic parameter were estimated for teat number of Danish Landrace by using Gibbs sampling. Total number of records was 9898. Analytical model included sex as fixed effect and additive genetic random effects. The posterior mean estimates of genetic variance, residual variance and heritability were 1.034±0.084,0.541±0.064,0.656±0.037, respectively. The correponding REML estimates were 1.036,0.539,0.658,respectively. There were no significant differences between posterior estimates and REML estimates ( P >0.05)....

Genetic parameter were estimated for teat number of Danish Landrace by using Gibbs sampling. Total number of records was 9898. Analytical model included sex as fixed effect and additive genetic random effects. The posterior mean estimates of genetic variance, residual variance and heritability were 1.034±0.084,0.541±0.064,0.656±0.037, respectively. The correponding REML estimates were 1.036,0.539,0.658,respectively. There were no significant differences between posterior estimates and REML estimates ( P >0.05). Several priors were used to examine their influence on inferences. The priors were influential because of the relatively small data size.

This paper introduces a new family of a prior distributions for four reliability growth testing scenarios with exponential failure data. The proposed prior is of conditional form, which can accord well with various actual situations in reliability growth tests. The expressions of corresponding conditional means and variances for all stages are obtained, and the relationship between the shape of a prior distributions and their parameters are discussed. These results are helpful for better incorporation of expert...

This paper introduces a new family of a prior distributions for four reliability growth testing scenarios with exponential failure data. The proposed prior is of conditional form, which can accord well with various actual situations in reliability growth tests. The expressions of corresponding conditional means and variances for all stages are obtained, and the relationship between the shape of a prior distributions and their parameters are discussed. These results are helpful for better incorporation of expert opinons. The posterior density and Bayesian estimators and Bayesian lower bound of the reliability at the end of the test are also given.