基于内核的因果结构学习独立性测试对功能数据的学习
Felix Laumann1, Julius von Kügelgen2,3, Junhyung Park2
1Department of Mathematics, Imperial College London, London SW7 2BX, UK.
Entropy (Basel, Switzerland)
|December 23, 2023
概括
这项研究为功能数据引入了新的统计测试,使连续测量中的独立性和因果发现成为可能. 这些方法扩展了现有的标准,如hsic和cpt,用于对时间或空间依赖数据进行可靠的分析.
科学领域:
- 统计 统计 统计 统计
- 机器学习 机器学习
- 因果推理因果推理
背景情况:
- 沿着连续维度 (时间,空间) 的测量在科学领域是常见的.
- 传统的独立性测试和因果学习方法与功能数据固有的依赖性作斗争.
- 现有的方法无法解释功能数据的顺,连续性.
研究的目的:
- 专门为功能数据开发双变量,联合和条件独立性的统计测试.
- 将希尔伯特-施密特独立性标准 (hsic) 和它的d-变量版本 (d-hsic) 扩展到函数变量.
- 引入一种基于函数数据的希尔伯特-施密特条件独立性标准 (hscic) 的新型条件变换测试 (cpt) 统计.
主要方法:
- 利用专门设计的内核来创建功能变量的独立性测试.
- 扩展了希尔伯特-施密特独立性标准 (hsic) 和它的d-变量版本 (d-hsic).
- 使用希尔伯特-施密特条件独立性标准 (hscic) 开发了条件变换测试 (cpt) 的新统计数据,并进行了优化规范化.
主要成果:
- 经验结果表明,在合成功能数据的拟议测试中,在尺寸和功率方面表现良好.
- 这些方法成功地将hsic和d-hsic的适用性扩展到功能数据.
- 新的cpt统计数据显示了功能数据条件独立性测试的有效性.
结论:
- 开发的统计测试为分析功能数据独立性提供了有效的工具.
- 这些方法有助于从连续的,时间或空间依赖的测量中学习因果结构.
- 该方法在合成和现实世界的社会经济数据集上得到了验证.
更多相关视频
09:01A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Published on: May 7, 2014
10.2K
08:05Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
Published on: June 30, 2020
7.6K
相关概念视频
01:21Introduction to Test of Independence
2.3K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
2.3K
01:16Hypothesis Test for Test of Independence
3.6K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
3.6K
01:09Functional Classification of Joints
4.1K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
4.1K
01:28Criteria for Causality: Bradford Hill Criteria - II
321
The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
321
01:21Causality in Epidemiology
424
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
424
01:11Types of Hypothesis Testing
26.4K
There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p...
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p...
26.4K