Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

947
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
947
Distance Problem01:29

Distance Problem

7
When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...
7
Properties of DTFT I01:24

Properties of DTFT I

735
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
735
Unusual Results01:16

Unusual Results

3.7K
Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
According to the range rule of thumb, any value above or below two standard deviations, 2σ  from the mean, μ  is considered unusual.
Maximum unusual value =...
3.7K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

527
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
527
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

561
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
561

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

An Entropy-Based Framework for Hybrid Coalitions in Game Theory-Part I: Human Arbitration.

Entropy (Basel, Switzerland)·2026
Same author

Entropic and algebraic transcript-based tools in time series analysis.

Chaos (Woodbury, N.Y.)·2026
Same author

Transcript-based estimators for characterizing interactions.

Chaos (Woodbury, N.Y.)·2026
Same author

Nonlinear Dynamics and Applications.

Entropy (Basel, Switzerland)·2025
Same author

Applications of Entropy in Data Analysis and Machine Learning: A Review.

Entropy (Basel, Switzerland)·2025
Same author

Generalized synchronization in the presence of dynamical noise and its detection via recurrent neural networks.

Chaos (Woodbury, N.Y.)·2024
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
查看所有相关文章

相关实验视频

Updated: Jan 16, 2026

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.9K

基于变换的距离组和组值的时间序列.

José M Amigó1, Roberto Dale1

  • 1Centro de Investigación Operativa, Universidad Miguel Hernández, 03202 Elche, Spain.

Entropy (Basel, Switzerland)
|September 27, 2025
PubMed
概括
此摘要是机器生成的。

这项研究介绍了使用 permutation metrics 的组距离,如 Cayley 和 Kendall tau 距离,适用于通过符号表示的时间序列分析.

关键词:
凯利和肯德尔之间的距离.凯利的定理 凯利的定理代数表示的代数表示.编辑距离 编辑距离有限集团是有限的.值为组的时间序列.顺序的模式 顺序的模式顺序的变换是可以的.时间序列分析分析时间序列分析转录 记录 记录 记录 记录

更多相关视频

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

27.2K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K

相关实验视频

Last Updated: Jan 16, 2026

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
07:59

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

1.9K
VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

27.2K
Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K

科学领域:

  • 集团理论 集团理论
  • 时间序列分析时间序列分析
  • 计算数学 计算数学 计算数学

背景情况:

  • 对称组是由函数组合下的顺序形成的.
  • 这些群体拥有代数结构和相关指标,如凯利和肯德尔的距离.
  • 有限组在象征时间序列表示,特别是顺序表示中是基本的.

研究的目的:

  • 介绍一个有限群体中距离的一般概念.
  • 为了利用基于 permutation 的距离 (Cayley,Kendall tau) 来进行组分析.
  • 探索这些距离在组值时间序列分析中的应用.

主要方法:

  • 使用凯利定理来建立对称组子组的组等态.
  • 定义和应用有限组内的基于 permutation 的距离.
  • 将计量概念扩展到组值时间序列.

主要成果:

  • 介绍了一个定义一般有限群的距离的框架.
  • 基于换的距离与基于传统发电机的距离的比较.
  • 证明这些度量工具在时间序列分析中的实用性.

结论:

  • 基于变的距离提供了一种新的方法来量化有限群体内的关系.
  • 开发的方法为分析复杂的时间序列数据提供了有价值的工具.
  • 该研究将抽象的群理论与实际的数据分析应用联系起来.