# Questions tagged [kernel-smoothing]

Kernel smoothing techniques, such as kernel density estimation (KDE) and Nadaraya-Watson kernel regression, estimate functions by local interpolation from data points. Not to be confused with [kernel-trick], for the kernels used e.g. in SVMs.

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### How obtain , using R code , the p-order quantile by inverting CDF estimated non-parametrically by kernel method [closed]

I try to estimate nonparametrically the p-order quantile by generalized inversion of the conditional distribution function from a program R. But I can't really find the solution. Could you help me to ...
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### Kernel density estimation and boundary bias

What sort of kernel density estimator does one use to avoid boundary bias? Consider the task of estimating the density $f_0(x)$ with bounded support and where the probability mass is not decreasing ...
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### Hat Matrix of Semiparametric Regression Model

In semiparametric regression, I have found very limited work which deals with Hat matrix. All available work is related to splines for nonparametric portion. Now I am trying to perform this with ...
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### Nonparametric regression - bias and variance [migrated]

TL;DR - will be glad if someone will help me write a code (preferably in MATLAB) that recovers the figure below using Gaussian kernel. I am particulary interested in understanding how to recover the ...
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### Sampling from dataset according to distribution obtained from another dataset

Suppose we have dataset $A$ with several categorical and numerical features: $A_{cat_1}$, $A_{cat_2}$, $\ldots;$ $A_{num_1}$, $A_{num_2}$, $\ldots;$ Also we have another dataset $B$ with the same ...
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### Find the CI for a given interval of HDI?

I'm working with big data that doesn't fit well to a distribution but often exhibits a peak (maybe two). I'm looking for a method to calculate the confidence for a given range around the mode. For ...
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### Smoothing histograms with kernel methods

I have a problem where I can receive as output, multidimensional counts in "histogram" form. I can also adjust the size of the bins I receive (i.e., many or few bins). I want to smooth the data and ...
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### Looking for a sample that proves that KDE behaves worse than the Dirichlet Process

I am trying to find an example that clearly shows that the kernel density estimator does worse than the Dirichlet process in terms of estimating the distribution of a sample. But eventually, I always ...
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### Recent advances in the use of the spectra of kernel integrals following Yoshua Bengio's 2004 paper that links kernel PCA and spectral clustering?

In Yoshua Belgio's 2003 technical report http://www.iro.umontreal.ca/~lisa/pointeurs/TR1232.pdf, and subsequent 2004 paper http://www.iro.umontreal.ca/~lisa/pointeurs/bengio_eigenfunctions_nc_2004.pdf,...
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### Gaussian kernel normalization/weights question (python), boundary correction?

I'm trying to decipher some code ... ...
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### Inferential properties of Two-Dimensional Kernel Density Estimation

In r, I create a 70% density contour from a two-dimensional kernel density estimation using ...
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### Does local linear regression include a weighting Kernel?

I am applying a Regression Discontinuity Design (RDD) to estimate the effect of a policy change. In RDD I can apply the parametric approach (polynomial regression) and the non-parametric approach (...
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### state of the art in density estimation

I have seen density estimation methods which are pretty old. Specifically, I am referring to Parzen Window method. When I read the original Parzen's paper, I was amazed by it's beauty and I know that ...
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### Kernel density, why does my subset appear to have a larger spread than the original series?

I have a series that is 1500 observations long called alt_intercept. From it, I created a subset that contains values only if another series (called pvalue) is less ...
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### why does y axis sometimes change from normal histogram to kernel density?

Consider the distributions I have plotted below. They are of the same variables, one in normal histogram form and another in kernel density (Epachanov). As far as I know, the auc of the kernel ...
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### Kernel Density Estimation - Physical Interpretation?

I just read this article about the motivation for KDE. From what I understand, you are using Gaussian probability density distributions for each datapoint and then, depending on the selected kernel ...
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### How can I estimate bivariate probability density for support restricted data?

I have a bivariate sample with the following kernel density estimation The issue is that there is actually a cutoff for log(Age) at about 2.5, so value greater than 2.5 has probability 0. The fitted ...
Suppose I have been given some data $X$ that I wish to resample according to their empirical distribution. For whatever reason, I decided to transform these variables to some other space $Y = f(X)$ ...
I need to compute mutual information gain based two continuous variables $X$ and $Y$ $I(X|Y) = \int_X\int_Y p_{x.y}(x,y) \log(\frac{p_{x.y}(x,y)}{p_{x}(x)p_{y}(y)})$. I have used Kernel Density ...