# 核分布

## 函数

 `fitdist` 对数据进行概率分布对象拟合 `distributionFitter` Open Distribution Fitter app `ksdensity` Kernel smoothing function estimate for univariate and bivariate data `mvksdensity` Kernel smoothing function estimate for multivariate data
 `cdf` 累积分布函数 `icdf` Inverse cumulative distribution function `iqr` Interquartile range `mean` Mean of probability distribution `median` Median of probability distribution `negloglik` Negative loglikelihood of probability distribution `pdf` 概率密度函数 `random` Random numbers `std` Standard deviation of probability distribution `truncate` Truncate probability distribution object `var` Variance of probability distribution

## 对象

 `KernelDistribution` Kernel probability distribution object

## 主题

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.

﻿