All Questions
14
questions
1
vote
0
answers
128
views
Gasser Müller estimator for estimating the derivative $m'(x)$ of a nonparametric regression function
I would like to compare the performance of the Gasser Müller estimator with other estimators for estimating the the derivative $m'(x)$ of the regression function $m(x)$.
Let's say we have the ...
- 111
2
votes
1
answer
737
views
Is Kernel-Regression parametric or non-parametric?
As the title says, is kernel regression a parametric or non-parametric method, and how can this be motivated/explained?
- 35
0
votes
0
answers
31
views
Biase of ASE estimation Kernel Regression
I'm trying to calculate the bias of the estimator $p(h)=n^{-1}\displaystyle\sum_{i=1}^{n}(Y_{j}-\hat{m}_{h}(X_{j})^{2}w(X_{j})$ of the averaged squared error. The result I find in the literature is ...
- 3
7
votes
0
answers
287
views
Minimizing MISE to find consistent estimator
Consider kernel regression estimation of the mean function $m$ of the process
$$y_t = m(x_t) + \epsilon_t,$$ where $\epsilon_t$' s are correlated with covariance function $R(s,t) = \exp \{-\lambda|s-...
- 765
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
39
views
Hypothesis testing in non-parametric regression
Say I have two processes/time series, $X = (X_{t_{1}},X_{t_{2}},\dots , X_{t_{n}})$ and $Y = (Y_{t_{1}},Y_{t_{2}},\dots , Y_{t_{n}})$ observed at times $t_i$ for $i=1,2,\dots, n$ where $0 < t_1 <...
- 31
12
votes
2
answers
6k
views
Is Kernel Regression similar to Gaussian Process Regression?
I've used Nadaraya-Watson Kernel regression before to smooth data. Recently I have run into Gaussian process regression.
Prima facie, they don't seem to be related. But I am wondering if there ...
- 38k
5
votes
1
answer
362
views
Nonparametric estimation of regression function: kernel estimation vs series estimation
I am working on a small research project trying to estimate regression function nonparametrically when I have only one regressor. Basically, I am trying to estimate the regression function
$$r(x)=E[Y∣...
- 578
5
votes
1
answer
752
views
Kernel Regression with Multiple Predictors
I know Kernel regression is a type of local regression, i.e., we consider nearby points/observations to predict the value at a particular point. In other words, we see which of the already existing ...
- 539
2
votes
1
answer
171
views
Is there an online way to compute additive, kernel or spline regressions?
I have an online learning problem where every second (say) I receive a new observation $(x_1,x_2,y)$. I'd like to fit the following models: $$ y = f(x_1) + f(x_2)$$ and maybe $$ y = f(x_1,x_2) $$
In ...
- 1,108
2
votes
0
answers
31
views
Local Kernel for Rate Data
Perhaps a naive question here. Is there a local kernel-based approach that is appropriate for modeling rate data of the form y/z, in which y can be 0 but z never is? Omitting z and measuring the mean ...
- 177
7
votes
1
answer
451
views
Kernel regression with monotonicity constraints
I need to fit a bivariate data using kernel regression (local polynomial regression).
It should satisfies two conditions.
$\frac{dy}{dx_1} \geq 0$ for all $x_2$
$\frac{dy}{dx_2} \geq 0$ for all $x_1$
...
- 1,097
3
votes
0
answers
2k
views
Which non-parametric regression could I apply to fit a curve to this data set?
I have posted a similar question about the same problem, having been suggested to use a polynomial Robust Linear Model, which worked fine for most cases, as can be seen here:
Non-algebric curve-...
- 273
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