Top "Kernel-density" questions

kernel density estimation is a non-parametric way to estimate the probability density function of a random variable.

R ggplot2 - Simple plot- cannot specify log axis limits

I'm trying to create a simple densityplot in R in ggplot2. Here's my code which works great. d <- …

r ggplot2 kernel-density
Peak of the kernel density estimation

I need to find as precisely as possible the peak of the kernel density estimation (modal value of the continuous …

r kernel-density
Using scipy.stats.gaussian_kde with 2 dimensional data

I'm trying to use the scipy.stats.gaussian_kde class to smooth out some discrete data collected with latitude and …

scipy multidimensional-array kernel-density
Specifying the scale for the density in ggplot2's stat_density2d

I'm looking to create multiple density graphs, to make an "animated heat map." Since each frame of the animation should …

r plot ggplot2 kernel-density
Integrate 2D kernel density estimate

I have a x,y distribution of points for which I obtain the KDE through scipy.stats.gaussian_kde. This …

python integration kernel-density probability-density
Weighted Gaussian kernel density estimation in `python`

Update: Weighted samples are now supported by scipy.stats.gaussian_kde. See here and here for details. It is currently …

python statistics scipy kernel-density
Compute area under density estimation curve, i.e., probability

I have a density estimate (using density function) for my data learningTime (see figure below), and I need to find …

r probability kernel-density probability-density density-plot
lower bound to kernel density estimation with seaborn for matplotlib in python

I have a collection of measured tree diameters and am trying to plot a histogram with a kernel density estimation …

python matplotlib kernel-density seaborn