fitdist | Ajustar el objeto de distribución de probabilidad a los datos |
distributionFitter | Open Distribution Fitter app |
ksdensity | Estimación de la función de suavizado del núcleo para datos univariados y bivariados |
mvksdensity | Kernel smoothing function estimate for multivariate data |
cdf | Función de distribución acumulativa |
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 | Función de densidad de probabilidad |
random | Números aleatorios |
std | Standard deviation of probability distribution |
truncate | Truncate probability distribution object |
var | Variance of probability distribution |
KernelDistribution | Kernel probability distribution object |
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.