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

Multiple Regression01:25

Multiple Regression

3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

129
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
129
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

96
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
96
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

182
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
182
Noncompartmental Analysis: Statistical Moment Theory00:56

Noncompartmental Analysis: Statistical Moment Theory

138
Noncompartmental analyses leverage statistical moment theory to examine time-related changes in macroscopic events, encapsulating the collective outcomes stemming from the constituent elements in play. Statistical moment theory is a mathematical approach used to describe the time course of drug concentration in the body without assuming a specific compartmental model. SMT provides insights into drug absorption, distribution, metabolism, and elimination by treating drug concentration versus time...
138
Correlation and Regression00:53

Correlation and Regression

1.3K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
1.3K

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

Siderophore-producing bacteria reduce soil cadmium bioavailability and alleviate cadmium stress in alfalfa.

Ecotoxicology and environmental safety·2026
Same author

A multi-modal co-attention model for accurate drug-target interaction prediction.

PloS one·2026
Same author

TriCloud: Drug-Target-Disease Ternary Network for Drug Repositioning Research Based on Point Cloud Modeling.

IEEE transactions on computational biology and bioinformatics·2026
Same author

Cortico-basal oscillations index naturalistic movements during deep brain stimulation.

Brain : a journal of neurology·2025
Same author

MDG-DDI: multi-feature drug graph for drug-drug interaction prediction.

BMC bioinformatics·2025
Same author

Heterogeneous effects of physical activity on physiological stress during pregnancy.

PLOS digital health·2025
Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
查看所有相关文章

相关实验视频

Updated: Jul 20, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K

多变量时间点过程回归.

Xiwei Tang1, Lexin Li2

  • 1Department of Statistics, University of Virginia, Charlottesville, VA.

Journal of the American Statistical Association
|July 31, 2023
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的点过程回归模型,用于分析复杂的神经元尖峰列车数据. 该方法有效地模拟了高维点过程,减少了维度,并改善了神经科学研究的解释.

关键词:
条件强度函数是一个条件强度函数.分离的维度是不同的维度.神经元尖峰火车的列车.规范化 规范化 规范化时间过程是时间过程.张量分解的张量分解

更多相关视频

Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.1K

相关实验视频

Last Updated: Jul 20, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.7K
Cross-Modal Multivariate Pattern Analysis
13:51

Cross-Modal Multivariate Pattern Analysis

Published on: November 9, 2011

20.0K
Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language
09:27

Using Eye Movements Recorded in the Visual World Paradigm to Explore the Online Processing of Spoken Language

Published on: October 13, 2018

10.1K

科学领域:

  • 计算神经科学是一种神经科学.
  • 统计建模 统计建模
  • 机器学习 机器学习

背景情况:

  • 在科学学科中,点处理数据越来越普遍.
  • 分析高维的神经元尖峰列车需要先进的统计方法.

研究的目的:

  • 为高维响应和预测数据提出一个新的点过程回归模型.
  • 解决缩小维度和解释复杂点过程关系的挑战.

主要方法:

  • 开发了一个点过程回归模型,以卷积方式使用基础转移函数.
  • 组织系数成一个三向张量,强加低级别,稀疏性和子组结构.
  • 设计了一个可扩展的优化算法来进行参数估计,并推导出理论保证.

主要成果:

  • 拟议的模型有效地减少了维度,并将信息整合到各个过程中.
  • 证明了准确的参数估计和一致的子组识别,即使尺寸不同.
  • 通过模拟和跨区域神经元尖峰列车的现实世界分析来验证.

结论:

  • 新型点过程回归模型为分析高维点过程数据提供了强大的工具,特别是在神经科学中.
  • 强加的张量结构提高了解释性和分析效率.
  • 该方法对复杂数据分析中的未来应用具有重大前景.