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

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

556
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
556
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

226
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
226
Response Surface Methodology01:16

Response Surface Methodology

171
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
171
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

72
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
72
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

122
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...
122
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

170
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,...
170

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

Octadecylamine-Modified CuO NPs Enabling Highly Selective <i>In Vivo</i> Ascorbic Acid Potentiometric Detection with Enhanced Sulfide Tolerance.

ACS sensors·2026
Same author

Root-Driven Reactive Oxygen Species Controls Multidimensional Arsenic Speciation in the Rice Rhizosphere.

Environmental science & technology·2026
Same author

A Note on Ising Network Analysis with Missing Data.

Psychometrika·2026
Same author

An efficient MCMC-INLA algorithm for Bayesian inference of logistic graded response models.

The British journal of mathematical and statistical psychology·2026
Same author

Hue<sub>v</sub>: A Tunable <i>Hue</i> Descriptor for the Quantitative Analysis of Multicolor Optical Sensors.

Analytical chemistry·2026
Same author

Radiotherapy Strategies for Stage II Breast Cancer With Lymphovascular Invasion After Mastectomy.

Anticancer research·2026
Same journal

Proficiency order invariance of MLE, MAP, EAP, and WLE in item response theory.

The British journal of mathematical and statistical psychology·2026
Same journal

Bias and precision in true-score estimation.

The British journal of mathematical and statistical psychology·2026
Same journal

Polychoric correlations under the assumption of elliptical latent traits.

The British journal of mathematical and statistical psychology·2026
Same journal

Regularized reduced rank regression for mixed predictor and response variables.

The British journal of mathematical and statistical psychology·2026
Same journal

A multiple-choice SDT model for cognitive diagnosis models.

The British journal of mathematical and statistical psychology·2026
Same journal

Modular item response and structural equation modelling via measurement and uncertainty preserving parametric modelling.

The British journal of mathematical and statistical psychology·2026
查看所有相关文章

相关实验视频

Updated: Jul 15, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

一个Gibbs-INLA算法用于多维分级响应模型分析.

Xiaofan Lin1, Siliang Zhang1, Yincai Tang1

  • 1KLATASDS-MOE, School of Statistics, East China Normal University, Shanghai, China.

The British journal of mathematical and statistical psychology
|September 29, 2023
PubMed
概括
此摘要是机器生成的。

一个新的Gibbs-INLA算法改进了对复杂的顺序数据的贝叶斯推理. 这种高效的方法提供了更高的准确性和处理大数据集,超过传统算法.

关键词:
吉布斯采样采样 吉布斯采样采样分级响应模型的分级响应模型集成嵌套拉普拉斯近似方法项目响应理论是物品响应理论.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K
Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

3.2K

相关实验视频

Last Updated: Jul 15, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K
Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury
07:21

Systems Analysis of the Neuroinflammatory and Hemodynamic Response to Traumatic Brain Injury

Published on: May 27, 2022

3.2K

科学领域:

  • 心理测量 心理测量 心理测量
  • 计算统计学 计算统计学

背景情况:

  • 顺序响应数据分析在心理学和教育等领域至关重要.
  • 多维物品响应理论 (MIRT) 模型复杂的响应模式.
  • 传统的贝叶斯推理方法 (例如,MCMC) 可能是计算密集的,需要广泛的调整.

研究的目的:

  • 在MIRT分级响应模型中引入一种新的Gibbs-INLA算法,用于高效的贝叶斯推理.
  • 为了解决分析大规模序列数据的现有方法的计算挑战和准确性限制.

主要方法:

  • 拟议的算法将吉布斯采样与集成嵌套拉普拉斯近似 (INLA) 结合起来.
  • 它旨在通过更少的代来减少计算内存和提高效率.
  • 通过模拟研究来评估性能,并与大都会-哈斯廷斯罗宾斯-蒙罗 (MH-RM) 算法进行比较.

主要成果:

  • 与MH-RM算法相比,Gibbs-INLA算法显示出更高的估计准确性.
  • 它在计算效率上提供了显著的改进,并且需要更少的计算内存.
  • 该算法有效地处理大型多维响应数据集.

结论:

  • 吉布斯-INLA算法为MIRT分级响应模型中的贝叶斯推理提供了一种计算效率高,准确的方法.
  • 这种新的框架适用于分析大型和复杂的顺序数据集,例如人格库存数据.
  • 对于更复杂的模型和不同的数据类型,存在潜在的扩展.