All Questions
11
questions
1
vote
0
answers
96
views
Time Varying Coefficient Model with Uniform Kernel and Spline Estimator
I'm working on the BMACS data set data(BMACS) from library(npmlda).
I'm looking at the the time-varying coefficient model of post-CD4 versus smoking $X_1$, pre-HIV CD4 percent $X_2$ (centered) and age ...
- 25
2
votes
0
answers
25
views
Contribution of a predictor in Nonparametric regression
Is there an equivalent to a beta weights in a nonparametric regression?
I am using the NP package in R and running a local linear regression where my bandwidth estimates are produced using least ...
1
vote
0
answers
575
views
Smooth quantile estimation algorithm
I came across the paper of M. C. Jones on smooth quantile estimation (link). He proposes using the following estimator for quantile function $Q$ around point $p$:
$$
\hat{Q}(p) = \sum_{i=1}^{n} X_{(i)}...
- 101
2
votes
1
answer
3k
views
Bootstrapping a Kernel Density: Help in interpreting R code
I found this excellent code snippet online which gives the code for boostrapping a kernel density estimate to get confidence bands. Now, I am not that well versed in R, and would like to know what's ...
- 587
9
votes
1
answer
2k
views
np package kernel density estimation with Epanechnikov kernel
I'm working with the "geyser" data set from the MASS package and comparing kernel density estimates of the np package.
My problem is to understand the density estimate using least squares cross-...
- 93
12
votes
1
answer
257
views
What is the name of the density estimation method where all possible pairs are used to create a Normal mixture distribution?
I just thought of a neat (not necessarily good) way of creating one dimensional density estimates and my question is:
Does this density estimation method have a name? If not, is it a special case of ...
- 6,840
6
votes
1
answer
653
views
State of the art: Non-parametric density estimation with a boundary and data clumped near zero [duplicate]
I have some data which I wish to estimate the marginal distribution of. I have no
real idea what parametric distribution would be suitable, so was planning on fitting a non-parametric (probably kernel)...
- 545
15
votes
1
answer
12k
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 ...
- 1,173
3
votes
1
answer
2k
views
What's the best Kernel Regression package in R?
I am looking for a good and modern Kernel Regression package in R, which has the following features:
It has cross-validation
It can automatically choose the "optimal" bandwidth
It doesn't have ...
- 2,355
3
votes
3
answers
724
views
How to estimate the mode using non-parametric methods of a 4-variate random vector drawn from a continuous multivariate distribution?
I have a sample of size 10,000 of a 4-variate random vector coming from a (unknown) continuous multivariate distribution.
How can I estimate the mode of this density using nonparametric methods?
I ...
- 31
4
votes
0
answers
1k
views
Conditional kernel density plot with R's np package [closed]
I tried to use the Kernel Density plot method from Hayfield and Racine (2008) np package for my own data, but somehow ended up with different type of plots and I ...
- 2,145