Probit analysis was developed by Chester in 1934.
概率元分析是由切斯特于1934年提出的。
The PROBIT architecture in an SOA world.
soa世界中的PROBIT体系结构。
Implementing the PROBIT architecture with IBM products.
使用IBM产品实现PROBIT体系结构。
Figure 4 represents the SOA view of the PROBIT architecture.
图4表示PROBIT体系结构的soa视图。
This high-level architecture forms the basis for the architecture of the PROBIT tool.
此高级体系结构形成了PROBIT工具体系结构的基础。
The next section describes in more detail the IBM products used to implement the PROBIT architecture.
下一个部分将更详细地描述用于实现 PROBIT 体系结构的IBM产品。
The connectivity layer mainly highlights a broker component within the context of the PROBIT architecture.
在PROBIT体系结构的上下文中，连接层主要突出体现了一个代理组件。
Predictive Real-time Business Intelligence Tool (PROBIT) : The architecture and vision of a situational awareness framework.
预测性实时业务智能工具(PROBIT)：环境感知性框架的体系结构和远景。
The regression analysis showed that there was significantly positive correlation between probit and logarithm of concentrations.
回归分析表明，两种离子的概率单位与浓度对数之间存在着极显著的正相关。
In addition, PROBIT utilizes the Generalized Publish and Subscribe Services (GPASS) ([1], [2]) to distribute events to event consumers.
此外，PROBIT还利用通用发布与订阅服务(GPASS)([1]、[2])将事件分发给事件使用者。
Finally, we'll present the NPA use case scenario from the IBM enterprise, and describe a reference implementation using PROBIT to manage the NPA process.
最后，我们将介绍来自IBM企业的NPA用例场景，并描述使用PROBIT来管理npa流程的参考实现。
We'll then present the architecture of our BEP framework, the Predictive Real-time Operational Business Intelligence Tool (PROBIT), which embodies the vision.
然后我们将介绍我们的CEP框架的体系结构，即体现该远景的预测性实时操作业务智能工具(Predictive Real - time Operational Business Intelligence Tool,PROBIT)。
There has been four kinds of main early warning models of exchange crisis at present, namely "signal" approach, probit model, cross-county regression model and subjective probability method.
目前已经出现了四种主要的外汇危机预警模型，即信号方法、概率单位方法、截面回归方法以及主观概率法。
To study influence factors of customer complaint, binary choice Probit model and binary choice Logit model of customer complaint are built, and two numerical examples are given, respectively.
对顾客抱怨的影响因素进行研究，分别构建了顾客抱怨的二元选择Logit、Probit模型，并给出了两个实例。
To study influence factors of customer complaint, binary choice Probit model and binary choice Logit model of customer complaint are built, and two numerical examples are given, respectively.
对顾客抱怨的影响因素进行研究，分别构建了顾客抱怨的二元选择Logit、Probit模型，并给出了两个实例。
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