ggdist:图形语法中的分布和不确定性的可视化
IEEE transactions on visualization and computer graphics
|October 26, 2023
概括
该ggdist R包增强了图形的语法,以更好地可视化不确定性. 它使用分布式可视化统一了各种不确定性类型,改善了贝叶斯式和频率主义方法的统计图形.
科学领域:
- 数据可视化 数据可视化
- 统计计算 统计计算
- 计算机图形 计算机图形
背景情况:
- 图形语法是许多可视化工具的基础,但缺乏对高级不确定性可视化的强有力的支持.
- 现有的不确定性可视化方法通常很难在当前图形框架的语法中实现.
- 研究已经开发出了新的不确定性可视化,不容易整合到标准工具包中.
研究的目的:
- 介绍ggdist,ggplot2图形工具包语法扩展,旨在提高不确定性可视化功能.
- 展示分布式可视化如何在一个框架内统一各种不确定性可视化类型.
- 探索使用信心分布的频率主义不确定性可视化的正式化.
主要方法:
- 开发了ggdist作为R.中gplot2包的一个扩展.
- 利用分布式可视化方法,将分布的函数映射到视觉道 (美学).
- 综合贝叶斯式和频率式不确定性可视化方法通过信心分布.
主要成果:
- ggdist提供了一个统一的框架,用于创建广泛的不确定性可视化,包括复杂类型.
- 分布镜头简化了各种不确定性可视化类型的表达.
- 该套件促进了贝叶斯式和频率式不确定性表示的整合.
结论:
- ggdist在图形范式的语法中显著增强了不确定性可视化.
- 分布可视化方法提供了一种强大而灵活的方法来表示不确定性.
- 从ggdist的开发中吸取的教训可以催化不确定性可视化实现的进一步进展.
相关概念视频
Probability Histograms
11.7K
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.
11.7K
Probability Distributions
7.2K
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...
7.2K
Ogive Graph
5.6K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
5.6K
Uncertainty: Overview
570
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
570
Histogram
13.8K
The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
13.8K
Uncertainty: Confidence Intervals
4.1K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
4.1K


