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Questions tagged [kernel-density]

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

Kernel density estimation is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. Kernel density estimates are closely related to histograms, but can be endowed with properties such as smoothness or continuity by using a suitable kernel

http://en.wikipedia.org/wiki/Kernel_density_estimation

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Kernel Density Estimation Heatmap in python

I have a list of latitude and longitude coordinates and respective Received Signal strength values at each coordinate. How would I plot a kernel density estimation (kde) 2D heatmap for these signal strengths at each lat-lon in python(matplotlib)?
Lion
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kernel density estimation python - Evaluation

I'm trying to augment the number of records of my dataset in order to make a semi-supervised learning algorithm. The starting dataset has around 495 record with 9 features and 2 targets. So far I've plot the distribution of the features in order to…
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Plot kernel density estimation with the kernels over the individual observations in R

Well to keep things short what I want to achieve is a plot like the right one: I would like to obtain a standard KDE plot with its individual kernels plotted over the observations. The best solution would be the one that considers all the different…
Deset
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Add a specific value of x-axis on ggplot

I am using the ggplot function to plot this kind of graph image I want to add the specific value of the x-axis as shown in the picture this is my code : quantiles <- quantile(mat,prob = quant) x <- as.vector(mat) d <-…
N.BY
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How to use KDE (Kernel density estimation) for one-dimensional array clustering, in scikit-learn?

I read several posts regarding 1D array clustering in which people are saying that clustering is not suitable for 1D array and that kernel density estimation should be used instead. However, nobody explained how to acctualy perform clustetring by…
zlatko
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Find all values such that .. from a density plot in Python

I plot(x,y) a chart, for which I want to find two things: - all values of x for which y>some specified value, - all values of y for which y>some specified value. How can I do it?
tesgoe
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Determine intervals from kernel density estimation

I have a 1-dimensional data which is (t) where users spend time to complete a task. I applied kernel density estimation from http://www.mathworks.com/matlabcentral/fileexchange/14034-kernel-density-estimator to remove the outliers who spent…
Saeed
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ggplotly: R, labeling trace names but keep one line

I'm creating a ggplotly for a dataframe that's very similar to diamonds. Here's what I have so far: ggplotly(ggplot(diamonds, aes(depth, colour = cut)) + geom_density() + xlim(55, 70)) It creates the following: When you hover over the trace it…
cooldood3490
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geom_density - customize KDE

I would like to use a different KDE method than stats::density which is used by stat_density/geom_density to plot a KDE for a distrubtion. How should I go about this?
saladi
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How to change the colours of the lateral kde plots of seaborn jointplot

I want to create a sns.jointplot that uses the standard colormap "Greens". The output of this standard colorcycle is too light for the lateral kde estimated densities. I would prefer the darker colours you get when you use the "BuGn_r" colormap. Is…
cattt84
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R - hexbinplot of two datasets

How can I visualize overlapping values among two datasets in R. Preferably, I like to use a Hexbinplot (http://www.everydayanalytics.ca/2014/09/5-ways-to-do-2d-histograms-in-r.html) Here I have a dataset with two variables. Variable A:…
JohnnyDeer
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How is adaptative.density() (spatstat) managing duplicated points and default f value

I can not find this information in the reference literature [1] 1)how adaptative.density() (package spatstat) manage duplicated spatial points. I have duplicated points exactly in the same position because I am combining measurements from different…
YDO
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Bayes Classification with Multivariate Parzen Window using Spherical Kernel

I'm having a problem implementing a Bayes Classifier with the Parzen window algorithm using a spherical (or isotropic) kernel. I am running the algorithm with test data containing 2 dimensions and 3 different classes (For each class, I have 10 test…
telefunken
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Kernel density estimation in seaborn for cyclic end points

I've got some data that has cyclic end points (the x-axis is longitude and hence 0 and 360 are the same point), but as far as I can tell seaborn.kdeplot doesn't have an option to specify cyclic end points. What would be the easiest away to do…
Damien Irving
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implementation of transformed KDE in R

I am following the steps at the end of this post to implement a transformed Kernel Density Estimate (KDE) on a bounded support [0,+inf[. We use the transformation trick to avoid the boundary bias of the traditional KDE on bounded support (in that…
Antoine
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