# Tagged Questions

31 views

### What is the minimum number of data points required for kernel density estimation?

What is the minimum number of data points required for a kernel density estimation to be considered non-misleading/acceptable/adequate? Is there a some rule based on how dispersed the data is? For ...
40 views

### strange density plot of p-value [duplicate]

I computed the T-score and P-value using t.test() for my data, and finally I've plotted the density of my p-value and I've got strange plot. I don't know, why I see ...
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### Kernel density estimation - application

What is the validity of using a kernel-density-estimation to compare model x observed data? In other words, if the KDE curve for the observed data looks like the KDE for the model forecast, can I use ...
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### Value for Kernel Density Estimation is > 1 [duplicate]

I have 80 2D data points (located here) and am trying to estimate the pdf at a point $x$ by using a multivariate kernel density estimate. The mean vector is $\mu = [0.0368418, 0.0157501]$ and ...
162 views

### Smooth a circular/periodic time series

I have data for motor vehicle crashes by hour of the day. As you would expect, they are high in the middle of the day and peak at rush-hour. ggplot2's default geom_density smooths it out nicely A ...
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### How to calculate confidence intervals using subsampling after a nonparametric estimator about the empirical distribution function?

I have a problem where I think subsampling is more appropriate than the bootstrap. (Reason in another post.) However, I found no quick reference on subsampling CIs, and my naive inversion of the ...
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### Is excess mass estimation smooth enough to bootstrap? At what rate might a bunching estimator converge?

The recent public finance literature often estimates relative excess mass around specific points of the earnings distribution ("kink points" or "notches" of tax schedules, say), and then bootstraps to ...
449 views

### Good methods for density plots of non-negative variables in R?

plot(density(rexp(100)) Obviously all density to the left of zero represents bias. I'm looking to summarize some data for non-statisticians, and I want to avoid ...
145 views

### Gaussian Kernel function vs normal distribution function

I read from this link and thought that kernel density functions are used for solving the unrealistic normal distributions or specification errors. But when I read the description of kernel density in ...
45 views

### Modeling multivariate density with semiparametric methods

I am trying to model (using R) the density of multivariate data conditioned on a few known parameters so I can simulate sampling from new sets of parameters. I have about 100,000 data points that ...
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### Mode estimation in high dimensions

Suppose we have a sample $\boldsymbol{x}_i$ for $i$ in $1,\dots, n$, from a $d$-dimensional unimodal density $f(\boldsymbol{x})$. I would like to estimate the mode of $f(\boldsymbol{x})$. The ...
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### 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 ...
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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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### Kernel density estimator that doesn't collapse in the tails

I have iid data-points $x_1, \dots, x_n$, generated by an unknown density $f(x)$. So far I have approximated $f(x)$ with a normal $N(\hat{\mu}, \hat{\sigma}^2 )$, where $\hat{\mu}$ and ...
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### How to explain how I divided a bimodal distribution based on kernel density estimation

I have a dataset of bimodal population. It contains a smaller peak, which is considered to be "bad", and a bigger peak. I try to separate the bad part of data from the rest of data. What I did was: ...
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### Is it legitimate to use a conditional PDF derived using kernel density estimation for hypothesis testing?

Suppose I have some sample $X$ drawn from some unknown multivariate distribution $F(A,B)$, and I want to test the null hypothesis that a particular point $x$ was drawn from $F$. Would it be ...
407 views

### how to read y axis in kernel density graph [duplicate]

I need to understand how to read kernel density graphs. How do you come up with the values in y-axis?
119 views

### Estimating probability density in Parzen windows

I came across an interesting paper about stability measure which can be used as evaluation metric for continuous data discretization. The stability measure is constructed from a series of estimated ...
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### Kernel density estimation on asymmetric distributions

Let $\{x_1,\ldots,x_N\}$ be observations drawn from an unknown (but certainly asymmetric) probability distribution. I would like to find the probability distribution by using the KDE approach:  ...
1k views

### What does the y axis in a kernel density plot mean? [duplicate]

Possible Duplicate: Probability distribution value exceeding 1 is OK? I thought the area under the curve of a density function represents the probability of getting an x value between a ...
247 views

### Explain Kernel density chart

I'm running simulation on a linear model. I get 1000 results and the results are put into a density chart. I do understand that the xaxis is the dependent variable and yaxis represent the kernel ...
1k views

### Is there an optimal bandwidth for a kernel density estimator of derivatives?

I need to estimate the density function based on a set of observations using the kernel density estimator. Based on the same set of observations, I also need to estimate the first and second ...
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### Estimate density from neighbor distances

Assuming I have a data set of known size, and there is one object that I want to test for being in an approximately uniform distributed region of the data set. For the query object, I know the $k$ ...
102 views

### How to estimate the intensity of a multidimensional point process?

Note that for a homogeneous point process the density is just a number, while for an in-homogeneous process it is a function. In addition, how can I distribute that function on a larger study region ...
145 views

### Multivariate non-parametric density estimation with many missing values

Apologies in advance if any of my terminology here is wrong, I'm not an expert in statistics. If I've made any mistakes, let me know and I'll correct them. The task I'm looking for some advice on ...
101 views

### Bandwidth value for vector of equal values in kernel density estimation

How to define the value of bandwidth when we have a vector where all the values is the same? In this case, IQR and sample variation are both equal zero and Silverman's rule also result in zero. ...
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### Area under the “pdf” in kernel density estimation in R

I am trying to use the 'density' function in R to do kernel density estimates. I am having some difficulty interpreting the results and comparing various datasets as it seems the area under the curve ...
443 views

### Density estimation with a truncated distribution?

I have some data which is clearly truncated on the left. I wish to fit it with a density estimation that will handle it in some way instead of trying to smooth it down. What known methods (as usual, ...
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### Constrained kernel density estimation

Suppose you are trying to estimate the joint density $p(x,y)$ based on observed $(X,Y)$. However, you know that the marginal density $p(x)$ is uniform. How can you use this information to improve ...