一个参数随机分布的比例跨学科应用:系统可靠性,医疗保健和能源消耗
Muhammad Ilyas1, Muhammad Mohsin1
1College of Statistical Sciences, University of the Punjab, Lahore, Pakistan.
Journal of applied statistics
|March 16, 2026
概括
这项研究引入了一个新的统计分布来建模现实世界的数据,提供了对系统可靠性,医疗保健和能源消耗的见解. 拟议的模型在各种应用中表现出强的性能.
科学领域:
- 统计建模 统计建模
- 可能性分布的概率分布.
- 随机过程是指随机的过程.
背景情况:
- 统计模型为主动策略量化不确定性.
- 双变条件韦布尔分布是比率建模的基础.
研究的目的:
- 引入一种新的一参数随机分布,用于比率数据.
- 从系统可靠性,医疗保健和能源消耗等方面建模各种数据集.
- 评估拟议的分布的统计属性和性能.
主要方法:
- 从双变量条件Weibull.一个参数的随机分布的推导.
- 模拟研究使用验收-拒绝方法来确定参数稳定性.
- 通过最大概率和贝叶斯方法进行参数估计.
- 在真实世界的数据上应用和与现有模型进行比较.
主要成果:
- 拟议的分布表现出有利的统计性质.
- 模拟结果显示了良好的参数估计稳定性.
- 该模型在各种应用中展示了与现有模型相比的能力.
- 估计的量值为可靠性,死亡率和能源消耗提供了洞察力.
结论:
- 新的随机分布有效地模拟了可靠性,医疗保健和能源部门的比率数据.
- 该模型为这些领域的决策提供了有价值的见解.
- 拟议的分布是对现有模型的一个有能力的替代方案.
相关概念视频
Probability Distributions
13.0K
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...
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
13.0K
Uniform Distribution
6.4K
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
Two essential properties of this distribution are
6.4K
Sampling Distribution
18.9K
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...
18.9K
Random Error
10.0K
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
10.0K
Distribution Reliability and Automation
558
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
558
Hazard Rate
473
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
473

