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

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

273
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...
273
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

3.0K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
3.0K
Poisson Probability Distribution01:09

Poisson Probability Distribution

12.1K
A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
The...
12.1K
Probability Distributions01:32

Probability Distributions

12.3K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
12.3K
Sampling Distribution01:12

Sampling Distribution

18.3K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
18.3K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

5.2K
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...
5.2K

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

Generalized Marshall-Olkin exponentiated exponential distribution: Properties and applications.

PloS one·2023
查看所有相关文章

相关实验视频

Updated: Feb 19, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.5K

用一般化的马歇尔-奥尔金-库马拉斯瓦米分布建模物理数据.

Selim Gündüz1, Egemen Ozkan2, Kadir Karakaya3

  • 1Department of Business Administration, Faculty of Business, Adana Alparslan Türkeş Science and Technology University, Adana, Türkiye.

PloS one
|February 17, 2026
PubMed
概括

引入了一个新的局限数据统计分布,为各种危险率提供灵活的建模. 它的参数使用多种方法进行估计,在医学,政治,物理和教育领域的现实应用中表现出强的性能.

科学领域:

  • 统计 统计 统计 统计
  • 可能性分布的概率分布.
  • 数学建模的数学建模

背景情况:

  • 传统的统计模型往往在有限的数据上扎.
  • 需要灵活的分布来捕捉不同的危险率形状.
  • 像Beta和Kumaraswamy这样的现有分布可能并不总是最佳的.

研究的目的:

  • 引入一个新的统计分布,定义在一个有界的间隔.
  • 检查新分布的属性,包括时刻和相关曲线.
  • 开发和评估参数估计技术和量子回归模型.

主要方法:

  • 引入了一个新的有限概率分布.
  • 调查的时刻,洛伦茨曲线和邦费罗尼曲线.
  • 使用最大概率,最小平方,安德森-达林,克拉梅尔-·米塞斯和间隔方法进行参数估计.
  • 进行蒙特卡洛模拟以评估估计性能.
  • 开发了局限依赖变量的一种定量回归模型.

主要成果:

  • 拟议的分布有效地模拟了各种危险率形状 (例如,反向浴,浴,增加,减少).
  • 评估了参数估计方法,并使用模拟指导性能评估.

更多相关视频

Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

11.6K
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

3.0K

相关实验视频

Last Updated: Feb 19, 2026

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level
06:55

Synthesis of Cyclic Polymers and Characterization of Their Diffusive Motion in the Melt State at the Single Molecule Level

Published on: September 26, 2016

8.5K
Assembly and Characterization of Polyelectrolyte Complex Micelles
08:44

Assembly and Characterization of Polyelectrolyte Complex Micelles

Published on: March 2, 2020

11.6K
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

3.0K
  • 新的分布证明了在医学,政治,物理和教育领域的真实世界数据中的适用性和灵活性.
  • 在特定的局限数据建模场景中表现优于Beta和Kumaraswamy分布.
  • 结论:

    • 新型分布提供了一个强大而灵活的工具来分析有限的数据.
    • 开发的量子回归模型增强了模拟有限依赖变量的能力.
    • 分布是一种可行的替代现有模型,在科学和教育领域具有广泛的适用性.