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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

38
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...
38
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

324
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
324
Quantifying and Rejecting Outliers: The Grubbs Test01:02

Quantifying and Rejecting Outliers: The Grubbs Test

1.4K
Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...
1.4K
Survival Tree01:19

Survival Tree

51
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
51
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.0K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.0K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

54
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...
54

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

Variational Bayes for High-Dimensional Multi-Source Heterogeneous Data With Sparse Priors.

Statistics in medicine·2026
Same author

The role of <i>Clostridium butyricum</i> and its metabolites in modulating gut mucosal immunity: implications for viral infections and inflammatory diseases.

Frontiers in immunology·2026
Same author

Intrinsic dual-emitting Si dots for high-precision and broad-range pH detection.

Analytica chimica acta·2025
Same author

Downregulation of FcRn promotes ferroptosis in herpes simplex virus-1-induced lung injury.

Cellular and molecular life sciences : CMLS·2025
Same author

Semiparametric normal transformation joint model of multivariate longitudinal and bivariate time-to-event data.

Statistics in medicine·2023
Same author

Variable selection for joint models of multivariate skew-normal longitudinal and survival data.

Statistical methods in medical research·2023
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: May 25, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.4K

被处罚的指数式倾斜概率,用于增加缺失数据的维度模型.

Xiaoming Sha1, Puying Zhao1, Niansheng Tang1

  • 1Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming 650050, China.

Entropy (Basel, Switzerland)
|February 26, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了处罚指数倾斜 (ET) 概率方法,用于在缺少数据的高维模型中进行参数估计和变量选择. 该方法确保准确的估计和假设测试,通过模拟和现实世界甲状腺数据分析进行验证.

关键词:
威尔克斯的房地产财产.估计方程 估计方程越来越多的维度模型随机失踪的人是随机失踪的人.被处罚的指数式倾斜的可能性.

更多相关视频

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

3.3K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.1K

相关实验视频

Last Updated: May 25, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

2.4K
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

3.3K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.1K

科学领域:

  • 统计 统计 统计 统计
  • 生物统计学 生物统计学
  • 计量经济学 计量经济学

背景情况:

  • 在高维模型中缺少数据会给估计和变量选择带来挑战.
  • 当处理随机缺失的响应时,现有的方法可能缺乏一致性或稳定性.
  • 准确的统计推断对于各种科学领域的复杂数据集至关重要.

研究的目的:

  • 开发一种新的处罚指数倾斜 (ET) 概率方法,用于同时进行参数估计和变量选择.
  • 为了解决在使用逆概率权重的增长维度模型中缺少响应数据的问题.
  • 为拟议的方法论建立强大的统计属性和假设测试能力.

主要方法:

  • 开发一个处罚的指数倾斜 (ET) 概率函数.
  • 应用逆概率加权 (IPW) 方法来处理缺失的响应数据.
  • 构建ET概率比统计数据,用于对参数进行假设测试.
  • 对估计器的一致性,非对称性属性和预言性属性的理论分析.

主要成果:

  • 拟议的惩罚性ET概率方法可以同时进行参数估计和变量选择.
  • 反向概率权重确保参数估计器的一致性,尽管缺少数据.
  • 在ET概率比率统计表明威尔克斯的属性用于假设测试.
  • 理论性质包括一致性和预言性质在特定条件下建立.

结论:

  • 被处罚的ET概率为缺少数据的高维统计建模提供了一个强大的工具.
  • 该方法提供可靠的参数估计和变量选择,增强统计推理.
  • 该方法通过模拟和对甲状腺数据的实际应用来验证,证明其有效性.