计算涉及多变量正常分布和多变量t分布,有或没有截断
Michael J Grayling1, Adrian P Mander1
1Hub for Trials Methodology Research, MRC Biostatistics Unit, Cambridge, UK.
概括
本研究介绍了多变量正常和非中心多变量t分布的高效计算工具. 这些方法可以准确计算关键的分布性质,即使有变量切断.
科学领域:
- 统计 统计 统计 统计
- 计算统计学 计算统计学
背景情况:
- 多变量正常和非中心的多变量t分布在统计建模中具有根本性的作用.
- 对于各种应用来说,有效计算它们的分布量至关重要.
研究的目的:
- 介绍新的命令和Mata函数用于评估分布式数量.
- 为了使多变量正常和非中心多变量t分布的有效计算.
主要方法:
- 开发专门的指挥和Mata功能.
- 实现计算密度,分布函数,等坐标量和伪随机向量的算法.
- 考虑具有和没有变量切断的场景.
主要成果:
- 对特定分布进行密度和分布函数的有效计算.
- 准确生成伪随机向量. 准确生成伪随机向量.
- 在计算中处理可变截断的能力.
结论:
- 开发的工具为分析这些复杂分布提供了强大而高效的解决方案.
- 这些功能对于统计分析和模拟的研究人员和从业人员来说都是有价值的.
相关概念视频
Estimating Population Mean with Unknown Standard Deviation
7.6K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
William S. Gosset (1876–1937) of the...
7.6K
Student t Distribution
5.9K
The population standard deviation is rarely known in many day-to-day examples of statistics. When the sample sizes are large, it is easy to estimate the population standard deviation using a confidence interval, which provides results close enough to the original value. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
The Student t distribution was developed by William S. Goset (1876–1937) of the...
The Student t distribution was developed by William S. Goset (1876–1937) of the...
5.9K
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
Choosing Between z and t Distribution
2.7K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.7K
Chi-square Distribution
3.6K
How does one determine if bingo numbers are evenly distributed or if some numbers occurred with a greater frequency? Or if the types of movies people preferred were different across different age groups or if a coffee machine dispensed approximately the same amount of coffee each time. These questions can be addressed by conducting a hypothesis test. One distribution that can be used to find answers to such questions is known as the chi-square distribution. The chi-square distribution has...
3.6K
Applications of Normal Distribution
4.9K
The normal distribution is a useful statistical tool. One of its practical applications is determining the door height after considering the normal distribution of heights of persons, such that many can pass through it easily without striking their heads. The normal distribution can also determine the probability of a person having a height less than a specific height.
The heights of 15 to 18-year-old males from Chile from 1984 to 1985 followed a normal distribution. The mean height is 172.36...
The heights of 15 to 18-year-old males from Chile from 1984 to 1985 followed a normal distribution. The mean height is 172.36...
4.9K


