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相关概念视频

Binomial Probability Distribution01:15

Binomial Probability Distribution

10.8K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.8K
Probability Distributions01:32

Probability Distributions

7.0K
 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...
7.0K
Uniform Distribution01:19

Uniform Distribution

5.0K
The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.
Two essential properties of this distribution are
5.0K
Poisson Probability Distribution01:09

Poisson Probability Distribution

8.1K
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...
8.1K
Probability Histograms01:17

Probability Histograms

11.6K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.6K
Normal Distribution01:11

Normal Distribution

11.0K
The normal, a continuous distribution, is the most important of all the distributions. Its graph is a bell-shaped symmetrical curve, which is observed in almost all disciplines. Some of these include psychology, business, economics, the sciences, nursing, and, of course, mathematics. Some instructors may use the normal distribution to help determine students’ grades. Most IQ scores are normally distributed. Often real-estate prices fit a normal distribution. The normal distribution is...
11.0K

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相关实验视频

Updated: Jul 7, 2025

How to Create and Use Binocular Rivalry
14:34

How to Create and Use Binocular Rivalry

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极端的桥梁:可逆双方向布分布.

Cira G Otiniano1, Eduarda B Silva1, Raul Y Matsushita1

  • 1Department of Statistics, University of Brasília, Brasília 70910-900, Brazil.

Entropy (Basel, Switzerland)
|December 23, 2023
PubMed
概括

一个新的可逆双模格姆贝尔分布模型既最大的和最小的极端. 这种多功能统计工具提供了一个简单的闭式函数,增强了其在金融和极端价值分析中的使用.

科学领域:

  • 统计 统计 统计 统计
  • 极端价值理论 极端价值理论
  • 金融数学 金融数学

背景情况:

  • 传统的极端值模型往往侧重于最大值或最小值,限制了它们在需要同时分析两者的场景中的应用.
  • 现有的双模格姆贝尔分布缺乏简单的闭式累积分布函数,这给计算带来了挑战.

研究的目的:

  • 介绍一个新的三参数可逆双模格姆贝尔分布.
  • 提供一个统计学上多功能工具,同时建模最大和最小极端.
  • 提高金融,水文和气象等领域的计算适用性.

主要方法:

  • 开发一种新型的三参数可逆双模格姆贝尔分布.
  • 一个简单的闭式累积分布函数的导数.
  • 分布性质的数学表述和图形说明.
  • 对风险价值 (VaR) 估计的财务数据的应用.

主要成果:

  • 拟议的分发提供了一个封闭形式的CDF,简化了计算.
  • 该模型有效地捕捉了同时发生的极端行为 (最大值和最小值).
  • 使用财务数据成功估计风险价值 (VaR) 证明了实际效用.
关键词:
甘贝尔的分销公司这是一种双模式的双模式.极端价值理论是一个极端价值理论.风险中的风险价值.

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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相关实验视频

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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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结论:

  • 可逆双模格姆贝尔分布是一个计算上具有吸引力和多功能工具,用于极端价值分析.
  • 它通过同时处理最大和最小极限来解决现有模型的局限性.
  • 该模型显示了其实用性,特别是在金融风险管理方面.