# Tagged Questions

kernel density estimation

48 views

### kde.test gives different p-values for similar KDEs

I have 4 sets of random floats between [0,1]: $d1, d2, d3, d4$. I need to compare these sets by pairs and I make use of the kde.test function of R's ...
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### Adding errors to Gaussian kernel density estimator

I'm using the scipy.stats.gaussian_kde function to generate a KDE from a set of $N$ points in a 2D space: $A = \{(x_1,y_1), (x_2,y_2), (x_3,y_2), ..., (x_N,y_N)\}$ ...
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### How to smear a histogram

I was asked to perform a Gaussian smearing on the bins of an histogram. What does this mean?
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### Integrating kernel density estimator in 2D

I'm coming from this question in case anybody wants to follow the trail. Basically I have a data set $\Omega$ composed of $N$ objects where each object has a given number of measured values attached ...
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### Kernel density estimation (KDE)

Due to an assignment I need to implement a algorithm based on KDE to schedule an input data in different servers. So far, I studied statistics in my bachelor but we did not go that far and they did ...
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### Confidence bounds for PDF

I build confidence bounds for estimating PDF of the empirical sample using bootstrapping: ...
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### Random sample using KDE or bootstrapping

I have an experimental sample, size of about 1000 values​​. I need to generate a much larger sample for simulation. I can create a samples like this: ...
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### Estimate PDF from only positive data [duplicate]

I have experemental data that not contain negative values (and theoretically can not contain negative values). When I do kernel density estimates of probability distribution function in ...
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### R: Density estimation vs Histogram Estimation

To draw random samples from a custom distribution, I recall reading that KDE's are better than histograms. (See hadley's comment here.) When I experimented in R, I am finding that the KDE method ...
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### Efficent global minimum search of costly to evaluate low dimensional error function

Trying to minimize the error from a probabilistic regression model which is composed of hierarchical KDE estimated PDFs. The top level is the result of 2-4 separate meta-PDFs from different data ...
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### kernel density estimation of a Dirichlet distribution

I have a Dirichlet distribution over the parameters of a multinomial, and I want to estimate its posterior density given some set of evidence. Due to some pecularities of my problem (e.g. presence of ...
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### Are Product KDEs proper density functions?

I have a fairly simple question about (multivariate) Kernel Density Estimators, but I somehow don't seem to find the answer anywhere: are these estimators supposed to specify a proper probability ...
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### Sheather-Jones bandwidth algorithm implementation in java?

The Sheather-Jones method for selecting an appropriate bandwidth for kernel density estimation generally produces better results than simpler methods such as Silverman's rule of thumb and Scott's ...