核分布

基于核函数拟合平滑分布并计算分布

Statistics and Machine Learning Toolbox™ 提供了多种处理核分布的方式。

要了解核分布，请参阅Kernel Distribution。

函数

`fitdist`	对数据进行概率分布对象拟合
`distributionFitter`	打开分布拟合器

`cdf`	累积分布函数
`gather`	Gather properties of Statistics and Machine Learning Toolbox object from GPU (自 R2020b 起)
`icdf`	逆累积分布函数
`iqr`	Interquartile range of probability distribution
`mean`	概率分布的均值
`median`	Median of probability distribution
`negloglik`	Negative loglikelihood of probability distribution
`pdf`	概率密度函数
`plot`	Plot probability distribution object (自 R2022b 起)
`random`	随机数
`std`	概率分布的标准差
`truncate`	Truncate probability distribution object
`var`	概率分布的方差

`ksdensity`	Kernel smoothing function estimate for univariate and bivariate data
`mvksdensity`	Kernel smoothing function estimate for multivariate data

KernelDistribution 核概率分布对象

Kernel Distribution
A kernel distribution is a nonparametric representation of the probability density function of a random variable.
Nonparametric and Empirical Probability Distributions
Estimate a probability density function or a cumulative distribution function from sample data.
Fit Kernel Distribution Object to Data
This example shows how to fit a kernel probability distribution object to sample data.
Fit Kernel Distribution Using ksdensity
This example shows how to generate a kernel probability density estimate from sample data using the ksdensity function.
Fit Distributions to Grouped Data Using ksdensity
This example shows how to fit kernel distributions to grouped sample data using the ksdensity function.