Kernel Distribution

Fit a smoothed distribution based on a kernel function and evaluate the distribution

Functions

fitdistFit probability distribution object to data
distributionFitterOpen Distribution Fitter app
ksdensityKernel smoothing function estimate for univariate and bivariate data
mvksdensityKernel smoothing function estimate for multivariate data
cdfCumulative distribution function
icdfInverse cumulative distribution function
iqrInterquartile range
meanMean of probability distribution
medianMedian of probability distribution
negloglikNegative loglikelihood of probability distribution
pdfProbability density function
randomRandom numbers
stdStandard deviation of probability distribution
truncateTruncate probability distribution object
varVariance of probability distribution

Objects

KernelDistributionKernel probability distribution object

Topics

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.