Questions tagged [nonparametric-density]
The nonparametric-density tag has no usage guidance.
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Measuring the Distance Between KDE Distributions with Different Bin Counts
I have two KDE distributions, each with a different number of bins. I'd like to compare them effectively, and I'm wondering if there's a recommended technique for this. Should I unify the number of ...
- 135
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Kernel Density Estimation, Bandwidth Tuning, Independence, and Comparison
like many of us here, I turn to kernel density estimation when I need a nonparametric estimate of a numerical feature's distribution, and in an attempt to assume as little as possible, I usually use ...
- 121
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Fast measure of "clusteredness" of points?
I have a cloud of points in a bounded volume in 2D (lets say 2d for now, though it'd be nice to generalize to any dimension):
$<p_n \in \mathbb [0, 1]^2: n \in [1..N]>$
I'm looking for some ...
- 614
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Parametric vs non-parametric generative models
I have a little perplexity trying to distinguish parametric vs non-parametric generative model.
In my understanding, a parametric generative model would try to learn the probability density function ...
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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 ...
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density function estimation in r
I firstly generate data from a bivariate normal distribution. Here comes the code.
...
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1
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2k
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Dealing with bimodal residuals
I want to run linear models to understand the effect of single predictors on an outcome. This is quite straightforward, but I am facing a situation where my residuals appear to be bimodal.
I can't ...
- 45
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Nonparametric Methods for Two Sample Quantile Test [duplicate]
Background
I want to compare two populations' quantile, e.g. 99.99% quantile, 95% quantile. So I am searching for methods for two sample quantile testing. Unfortunately, the population does not obey ...
- 227
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Optimal rate of convergence of nonparametric density estimators
Suppose that $X_1, X_2, \dots, X_n$ forms an independent and identically distributed sample from some $d$-dimensional probability distribution with unknown probability density function $f$. Let $x$ be ...
- 140
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How to write a joint kernel density of two random variables with known individual densities?
Consider two random variables $X$ and $Y$ with densities
$${f}_1(x) = \frac{1}{n_1h_1} \sum\limits_{i=1}^{n_1}K\left(\frac{x-u_i}{h_1}\right) ~~~~\text{and} ~~~~ {f}_2(y) = \frac{1}{n_2h_2} \sum\...
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Driver based forecasting using past distributions
I have reduced my original forecasting problem (Short context : I need to forecast hotel bookings and checkins for the next 3 months. I already have a reasonable forecast for bookings and need to ...
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what are the Kernels with zero variance (in KDE)?
I am studying about Kernels in Kernel Density Estimation and I came to understand that the bigger the $n$ that satisfies $\int_{-\infty}^{\infty}K(u)\cdot u^{j}du=0$ for all $1\leq j \leq n$ the more ...
- 63
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Density plot with epanechnikov with exceedance data
I'm trying to replicate empirical density plot from the paper "Computing Maximum Likelihood Estimates for the Generalized Pareto Distribution".
The data is ...
- 8,445
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Computation of the density of the ratio of two random variables
Background:
For two continuous random variables, $X$ and $Y$, the density of $Z := \frac{X}{Y}$ is given by
\begin{equation}
p_Z(z) = \int_{-\infty}^\infty \lvert y\rvert\, p_{XY}(zy, y) \, \text{...
- 111
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Is it necessary to normalize the dataset before kernel density estimation?
Is it necessary to normalize (Z-score) the dataset (high dimension) when the dimensionality of features varies greatly?
If I normalize the dataset, then the probability density (f1) obtained by KDE ...
- 96