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相关概念视频

Poisson Probability Distribution01:09

Poisson Probability Distribution

8.2K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
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Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

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The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
2.5K
Cluster Sampling Method01:20

Cluster Sampling Method

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Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
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Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

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The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
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Poisson's Ratio01:23

Poisson's Ratio

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Poisson's ratio is a material property that indicates their stress response. It explains the connection between the elongation or compression a material undergoes in the direction of an applied force and the contraction or expansion it experiences perpendicular to that force. When a slender bar is loaded axially, it stretches in the direction of the force and contracts laterally. Poisson's ratio is the negative ratio of this lateral contraction to the axial elongation. The negative sign...
470
Stratified Sampling Method01:16

Stratified Sampling Method

12.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
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相关实验视频

Updated: Jul 14, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
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Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

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在Poisson辅助平滑稀疏张量分解计数数据中检测热点.

Yujie Zhao1, Xiaoming Huo2, Yajun Mei2

  • 1Biostatistics and Research Decision Sciences Department, Merck & Co., Inc, North Wales, PA, USA.

Journal of applied statistics
|October 9, 2023
PubMed
概括

我们开发了Poisson辅助的光滑稀疏张量分解 (PoSSTenD) 来检测和定位传染病热点. 该方法分析了空间,时间和分类计数数据,以便及时进行公共卫生干预.

关键词:
这就是CUSUM CUSUM.热点检测检测热点的检测.普森回归是一种回归式.时间空间模型的模型.张量分解的分解方式

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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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相关实验视频

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科学领域:

  • 公共卫生监督 公共卫生监督
  • 生物统计学 生物统计学
  • 数据科学数据科学数据科学

背景情况:

  • 来自生物监测和医疗保健应用程序的计数数据对于监测传染病至关重要.
  • 及时检测和定位传染病热点对于有效的公共卫生反应至关重要.

研究的目的:

  • 为了引入一种新的方法,Poisson辅助了光滑稀疏张量分解 (PoSSTenD),用于检测和定位传染病热点.
  • 为在疾病监测中分析时空类别计数数据提供一个强大的框架.

主要方法:

  • 将计数数据表示为一个三维张量 (空间,时间,分类).
  • 将张量纳入波桑回归模型,将传染率分解为全球趋势和当地热点.
  • 使用累积总和 (CUSUM) 控制图来检测热点,并使用 LASSO 类型的稀疏估计来定位.

主要成果:

  • 该PoSSTenD方法成功地检测和定位传染病热点.
  • 通过数值模拟和美国传染病真实数据集的验证证明了该方法的有效性.

结论:

  • PoSSTenD为增强传染病监测系统提供了一个强大的工具.
  • 该方法允许快速识别异常感染率,促进有针对性的公共卫生干预.