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公开(公告)号：US20170024242A9
公开(公告)日：2017-01-26
申请号：US14270783
申请日：2014-05-06
Applicant: SAS Institute Inc.
Inventor： Xilong Chen , Mark Roland Little
CPC classification number: G06F9/46 , G01D21/00 , G06F9/455 , G06F17/17 , G06F17/175 , G06F17/18 , G06F17/30286 , G06F19/00 , H04L67/10
Abstract: Techniques to manage virtual classes for statistical tests are described. An apparatus may comprise a simulated data component to generate simulated data for a statistical test, statistics of the statistical test based on parameter vectors to follow a probability distribution, a statistic simulator component to simulate statistics for the parameter vectors from the simulated data with a distributed computing system comprising multiple nodes each having one or more processors capable of executing multiple threads, the simulation to occur by distribution of portions of the simulated data across the multiple nodes of the distributed computing system, and a distributed control engine to control task execution on the distributed portions of the simulated data on each node of the distributed computing system with a virtual software class arranged to coordinate task and sub-task operations across the nodes of the distributed computing system. Other embodiments are described and claimed.
Abstract translation: 描述了管理用于统计测试的虚拟类的技术。 设备可以包括模拟数据组件以产生用于统计测试的模拟数据，基于参数向量的统计测试的统计量来跟随概率分布，统计仿真器组件来模拟来自具有分布式的模拟数据的参数向量的统计 包括多个节点的计算系统，每个节点具有能够执行多个线程的一个或多个处理器，所述仿真通过分布在所述分布式计算系统的所述多个节点上的所述模拟数据的部分进行发生，以及分布式控制引擎，用于控制所述多个节点上的任务执行 分布式计算系统的每个节点上的模拟数据的分布部分具有布置成在分布式计算系统的各节点之间协调任务和子任务操作的虚拟软件类。 描述和要求保护其他实施例。
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公开(公告)号：US20210073023A1
公开(公告)日：2021-03-11
申请号：US16952375
申请日：2020-11-19
Applicant: SAS Institute Inc.
Inventor： Xilong Chen , Mark Roland Little
Abstract: Techniques to manage virtual classes for statistical tests are described. An apparatus may comprise a simulated data component to generate simulated data for a statistical test, statistics of the statistical test based on parameter vectors to follow a probability distribution, a statistic simulator component to simulate statistics for the parameter vectors from the simulated data with a distributed computing system comprising multiple nodes each having one or more processors capable of executing multiple threads, the simulation to occur by distribution of portions of the simulated data across the multiple nodes of the distributed computing system, and a distributed control engine to control task execution on the distributed portions of the simulated data on each node of the distributed computing system with a virtual software class arranged to coordinate task and sub-task operations across the nodes of the distributed computing system. Other embodiments are described and claimed.
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Patent Agency Ranking
公开(公告)号：US20200293360A1
公开(公告)日：2020-09-17
申请号：US16835854
申请日：2020-03-31
Applicant: SAS Institute Inc.
Inventor： Xilong Chen , Mark Roland Little
Abstract: Techniques to manage virtual classes for statistical tests are described. An apparatus may comprise a simulated data component to generate simulated data for a statistical test, statistics of the statistical test based on parameter vectors to follow a probability distribution, a statistic simulator component to simulate statistics for the parameter vectors from the simulated data with a distributed computing system comprising multiple nodes each having one or more processors capable of executing multiple threads, the simulation to occur by distribution of portions of the simulated data across the multiple nodes of the distributed computing system, and a distributed control engine to control task execution on the distributed portions of the simulated data on each node of the distributed computing system with a virtual software class arranged to coordinate task and sub-task operations across the nodes of the distributed computing system. Other embodiments are described and claimed.
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公开(公告)号：US09928320B2
公开(公告)日：2018-03-27
申请号：US15485577
申请日：2017-04-12
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described herein. Embodiments may include receiving, at a master node of a distributed system, a compound model specification comprising frequency models, severity models, and one or more adjustment functions, wherein at least one model of the frequency models and the severity models depend on one or more regressor and distributing the compound model specification to worker nodes of the distributed system, each of the worker nodes to at least generate a portion of samples for use in predicting compound distribution model estimates. Embodiments may also include predicting the compound distribution model estimates based on the sample portions of aggregate values and adjusted aggregate values.
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公开(公告)号：US20180060470A1
公开(公告)日：2018-03-01
申请号：US15805774
申请日：2017-11-07
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described herein. Embodiments may include receiving a compound model specification comprising a frequency model and a severity model, the compound model specification including a model error comprising a frequency model error and a severity model error, and determining a number of frequency models and severity models to generate based on the received number of models to generate. Embodiments include generating a plurality of frequency models through perturbation of the frequency model according to the frequency model error, and generating a plurality of severity models through perturbation of the severity model according to the severity model error. Further, embodiments include dividing generation of a plurality of compound model samples among a plurality of distributed worker nodes, and receiving the plurality of compound model samples from the distributed worker nodes, and generating aggregate statistics from the plurality of compound model samples.
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16.发明授权公开(公告)号：US09710428B2
公开(公告)日：2017-07-18
申请号：US14210301
申请日：2014-03-13
Applicant: SAS Institute Inc.
Inventor： Christian Macaro , Jan Chvosta , Mark Roland Little
Abstract: Techniques for automated Bayesian posterior sampling using Markov Chain Monte Carlo and related schemes are described. In an embodiment, one or more values in an accuracy phase for a system configured for Bayesian sampling may be initialized. Sampling may be performed in the accuracy phase based upon the one or more values to generate a plurality of samples. The plurality of samples may be evaluated based upon one or more accuracy criteria. The accuracy phase may be exited when the plurality of samples meets the one or more accuracy criteria. Other embodiments are described and claimed.
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17.发明申请TECHNIQUES FOR ESTIMATING COMPOUND PROBABILITY DISTRIBUTION BY SIMULATING LARGE EMPIRICAL SAMPLES WITH SCALABLE PARALLEL AND DISTRIBUTED PROCESSING 审中-公开通过模拟具有可分级并行和分布式处理的大型实验样本估算化合物概率分布的技术公开(公告)号：US20160314226A1
公开(公告)日：2016-10-27
申请号：US15197691
申请日：2016-06-29
Applicant: SAS Institute Inc.
Inventor： Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described. An apparatus comprising a configuration component, perturbation component, sample generation controller, an aggregation component, a distribution fitting component, and statistics generation component. The configuration component operative to receive a compound model specification and candidate distribution definition. The perturbation component operative to generate a plurality of models from the compound model specification. The sample generation controller operative to initiate the generation of a plurality of compound model samples from each of the plurality of models. The distribution fitting component to generate parameter values for the candidate distribution definition based on the compound model samples. The statistics generation component to generate approximated aggregate statistics.
Abstract translation: 描述估计复合概率分布的技术。 一种包括配置组件，扰动组件，样本生成控制器，聚合组件，分布拟合组件和统计生成组件的设备。 配置组件可操作以接收复合模型规范和候选分配定义。 扰动分量可用于从复合模型规范生成多个模型。 样本生成控制器用于从多个模型中的每个模型开始产生多个复合模型样本。 分布拟合组件，用于基于复合模型样本生成候选分布定义的参数值。 生成近似聚合统计信息的统计生成组件。
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