All Questions
15
questions
1
vote
0
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40
views
How to show $\sup_{x\in [a,b]}|f_n(x)-f(x)|=O_p(\sqrt{\frac{\log n}{nh}}+h^2)$ when the kernel $K(\cdot) $ is of bounded variation?
Consider the kernel estimate $f_n$ of a real univariate density defined by $$f_n(x)=\sum_{i=1}^{n}(nh)^{-1}K\left\{h^{-1}(x-X_i)\right\}$$
where $X_1,...,X_n$ are independent and identically ...
- 31
1
vote
0
answers
251
views
Bias of kernel density estimator of pdf $f$, where $f$ has bounded first derivative $f'$
Let's say the kernel density estimator is given by
$$\hat f(x) = \frac{1}{nh_n} \sum_{i=1}^n K\left(\frac{X_i-x}{h_n}\right),$$ where $h_n \to 0$, $nh_n \to \infty$, $K$ a symmetric probability ...
- 636
0
votes
0
answers
40
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Kernel Density Estimator: Misunderstanding in Taylor Series and the bias of KDE [duplicate]
Let's say the kernel density estimator is given by
$\hat f(x) = \frac{1}{nh_n} \sum_{i=1}^n K(\frac{X_i-x}{h_n})$, where $h_n \to 0$, $nh_n \to \infty$, $K$ a symmetric probability distribution ...
- 636
0
votes
0
answers
50
views
How to prove symmetry of a Uniform kernel?
I am trying to prove this kernel is valid,
$$
K(x) = \frac{1}{2}I(-1 < x < 1)
$$
So far I can integrate to 1, but how do I prove $$k(x) = k(-x)$$
Also, how do we satisfy that k(x) is $\ge$ 0 for ...
1
vote
0
answers
274
views
histogram vs. kernel in density estimation
Assume we have a problem of estimation of a density $f(x)$ over an interval $[0, 1]$. Can a regular histogram (i.e. with equal-sized bins) be viewed as some kind of a kernel?
- 676
1
vote
1
answer
353
views
How Parzen window density estimate $f_n$ converges to f
I am trying to understand how Parzen window density estimate converges to actual density function f(x).[Actually i am trying to learn machine learning on my own using available free resources. Please ...
2
votes
1
answer
839
views
Convergence of kernel density estimate as the sample size grows
Let $X\sim\text{Normal}(0,1)$ and let $f_X$ be its probability density function. I conducted some numerical experiments in the software Mathematica to estimate $f_X$ via a kernel method. Let $\hat{f}...
- 285
5
votes
1
answer
698
views
Expected value and variance of KDE
I need to find the expected value and variance of KDE given that $$(i) E[u] = 0 \to \int u\phi(u)du=0\\
(ii)V[u] = \sigma^2 \to \int u^2\phi(u)du=\sigma^2$$ where $\phi$ is the kernel function.
I've ...
- 361
4
votes
1
answer
1k
views
Properties of Kernel Density Estimators
Given
Let $X \in \mathbb{R}$ be a real-valued random variable with theoretical probability density function (pdf) $f(x)$ and corresponding cumulative distribution function (cdf) $F(x)$. Let $X_1, X_2,...
- 335
2
votes
1
answer
183
views
What are some of the common techniques for density estimation?
I'm trying to estimate the probability density function of a real random variable given its iid realizations. What are some of the standard techniques to do this?
One method I have heard of is the ...
9
votes
2
answers
3k
views
Estimating the gradient of log density given samples
I am interested in estimating the gradient of the log probability distribution $\nabla\log p(x)$ when $p(x)$ is not analytically available but is only accessed via samples $x_i \sim p(x)$.
There ...
- 563
2
votes
1
answer
840
views
Scaling up the bandwidth for kernel density estimation
Suppose I have $(\mathbf{X}_1, \cdots, \mathbf{X}_n)$ from a multivariate distribution $f$. The multivariate KDE is
\begin{align*}
\widehat{f}_\mathbf{H}(\mathbf{x}) = n^{-1}\sum_{i=1}^{n}K_\mathbf{H}(...
- 621
3
votes
3
answers
223
views
Literature on nonparametric density estimation
I am about to write my bachelor thesis about non-parametric density estimation, especially kernel density estimators and their application in classification. As I am quite new to looking for academic ...
- 33
16
votes
3
answers
5k
views
Where is density estimation useful?
After going through some slightly terse mathematics, I think I have a slight intuition of kernel density estimation. But I am also aware that estimating multivariate density for more than three ...
- 469
4
votes
3
answers
251
views
Fast multivariate unimodal density estimator
I have a sample $\boldsymbol{x}_i$ for $i$ in $1,\dots, n$, from a $d$ dimensional density $f(\boldsymbol{x})$ and I would like to estimate this unknown density. In addition I know that $f(\boldsymbol{...
- 3,264