kde: Kernel Density Estimation (KDE)
In DER: Income Polarization Index
Kernel Density Estimation R Documentation
Kernel Density Estimation (KDE)
Description
Kernel density estimation of a univariate sample using a Gaussian kernel.
Usage
kde(y, h, ncores = 1)
Arguments
y
A numeric vector containing the sample data.
h
A numeric value for boundwidth.
ncores
The number of cores to use. If greater than 1, parallel computing will take
place. It is advisable to use it if you have many observations and or many
variables, otherwise it will slow down the process. The default is 1, meaning
that code is executed serially.
Details
The kernel density estimate (KDE) provides a smooth estimate of the probability
density function of the sample data. In this implementation, the KDE is
evaluated only at the observed sample points themselves.
Value
A numeric vector of density estimates corresponding to each observation in y.
Author(s)
Michail Tsagris and Christos Adam.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr
and Christos Adam econp266@econ.soc.uoc.gr.
Examples
set.seed(123)
y <- rnorm(200)
dens <- kde(y, h = 1)
DER documentation built on Nov. 13, 2025, 1:07 a.m.
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| Kernel Density Estimation | R Documentation |
Kernel Density Estimation (KDE)
Description
Kernel density estimation of a univariate sample using a Gaussian kernel.
Usage
kde(y, h, ncores = 1)
Arguments
y |
A numeric vector containing the sample data. |
h |
A numeric value for boundwidth. |
ncores |
The number of cores to use. If greater than 1, parallel computing will take place. It is advisable to use it if you have many observations and or many variables, otherwise it will slow down the process. The default is 1, meaning that code is executed serially. |
Details
The kernel density estimate (KDE) provides a smooth estimate of the probability density function of the sample data. In this implementation, the KDE is evaluated only at the observed sample points themselves.
Value
A numeric vector of density estimates corresponding to each observation in y.
Author(s)
Michail Tsagris and Christos Adam.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Christos Adam econp266@econ.soc.uoc.gr.
Examples
set.seed(123)
y <- rnorm(200)
dens <- kde(y, h = 1)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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