先验分布

Through the modification of the present model, the uniform distribution was supplanted by the original image distribution and a priori probability updating was added in order to approach the realistic distribution.

通过对已有的模型进行改进，将原始信号分布代替均匀分布并增加了先验概率的迭代，使得分布情况更符合实际。

This method has some virtues comparing with the former two methods: First, temperature field could be computed without experiments if power dissipation of components is known, that means it can be apriority.

这种方法较采用有限元与有限差分法模拟温度场分布有几个优点，首先，如果元器件功耗已知，温度场的分布可以在不做实验的情况下就计算求得，做到了真正的先验性。

Since the Dirichlet distribution is the conjugate prior of the multinomial distribution, the beta distribution is the conjugate prior of the binomial distribution.

自的Dirichlet分布是共轭先验的多项分布， Beta分布是共轭先验的二项分布。

Based on the concept of the prior distribution, the Gamma distribution was introduced as the prior models of the unknown model parameters.

基于共轭先验理论，提出以伽马分布作为未知参数的先验模型，准确估计参数。

For the first time, from mathematics approach, the prior probability distribution of risk analysis was derived by the use of POME in two cases that were discrete and continuous information source.

首次分离散信源和连续信源两种情况，从数学途径阐述了POME在确定风险分析先验概率分布中的应用，以确定几种常用分布及估计其参数为例加以了解释。

For the first time, based on POME, two weighted generalized distances were defined to build up two fuzzy, which used relative membership degree, and optimal models for evaluation of water environment, considering both the randomness and the fuzziness.

首次分离散信源和连续信源两种情况，从数学途径阐述了POME在确定风险分析先验概率分布中的应用，以确定几种常用分布及估计其参数为例加以了解释。

For instance, if the life distribution of a certain kind of product is unaware, we stochastically choose products to do the time-truncated reliability test.

在Bayes方法中，提出了R的先验分布的构造方法——增函数法，并给出了在无失效数据问题中的应用。

Through the considering of two kinds of prior information—conjugate priorand noninformative prior,and by use of the method of Bayesian analysis,we obtain that the posteriordistribution of parameter in the model is approximate to Normal distribution.

考虑两类先验信息，即共轭先验和无信息先验，利用贝叶斯分析方法，得到模型参数的后验分布近似为正态分布。

Monte Carlo is a method that approximately solves mathematic or physical problems by statistical sampling theory. When comes to Bayesian classification, it firstly gets the conditional probability distribution of the unlabelled classes based on the known prior probability. Then, it uses some kind of sampler to get the stochastic data that satisfy the distribution as noted just before one by one. At last, it can obtain the posterior probability distibution of each unlabelled classes by analysing these stochastic data.

蒙特卡罗是一种采用统计抽样理论近似求解数学或物理问题的方法，它在用于解决贝叶斯分类时，首先根据已知的先验概率获得各个类标号未知类的条件概率分布，然后利用某种抽样器，分别得到满足这些条件分布的随机数据，最后统计这些随机数据，就可以得到各个类标号未知类的后验概率分布。

Firstly, we test that the error data are not normal distribution, and even the expectation is not zero. Then we analyze the possible type distribution of these error data. Finally, we use the stepwise method to fit the error data and obtain a function for some parameters of the SAIL model. As prior knowledge, the fitting function will be used to inverse these parameters ofthe SAIL model soon.

首先检验了误差数据不服从正态分布，甚至均值不为零；然后对误差数据可能服从的分布类型给予了解析，得到了指数分布和混合正态分布两种不同类型的可能分布；最后拟合了误差关于SAIL模型部分参数的函数表达式，以作为先验知识应用于反演之中。

Breath, muscle contraction of the buttocks; arch body, as far as possible to hold his head, right leg straight towards the ceiling (peg-leg knee in order to avoid muscle tension).

呼气，收缩臀部肌肉；拱起身体，尽量抬起头来，右腿伸直朝向天花板（膝微屈，以避免肌肉紧张）。

The cost of moving grain food products was unchanged from May, but year over year are up 8%.

粮食产品的运输费用与5月份相比没有变化，但却比去年同期高8％。