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### Nadaraya-Watson regression alternative for binary outcome

I am looking for pointers as to what would be the non-parametric equivalent of Nadaraya-Watson regression when modelling a binary outcome. I have been googling and ended up with Generalized Additive ...
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### why is the nadaraya watson estimator unbiased?

Say I have the model $Y_{i} = m(x_{i}) + \epsilon_{i}$ and $Y_{i}$ and $X_{i}$ are two mutually independent i.i.d. sequences. Then, how can I show that the Nadaraya Watson estimator is unbiased for ...
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### The nonparametric estimation in generalized regression model

Let $Y_t \in \mathbb{R}$ be a response variable and $X_t$ a $d$-dimensional explanatory variable. Assume we observe the process that $(X_1, Y_1), \cdots, (X_n, Y_n)$. \begin{equation} Y_{t} = \mu(...
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### In kernel regression, what are the common theoretical motivations for using a kernel that is Lipschitz continuous?

I read a few papers on Nadaraya-Watson kernel regression in which I saw assumptions that require the kernel function being Lipschitz continuous without explanation ( and without citation of such ...
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### Suppose $\widehat{m}'(x)$ is the derivative of Nadaraya-Watson estimator, can I get its uniform rate from the rate for its numerator and denominator?

Suppose $E(Y|x)=m(x)$ is the regression function that is twice differentiable, $f(x)$ is the density of $X$ that is also twice differentiable. Suppose $Y_i=m(X_i)+e_i$. $m'(x)$ is the derivative of ...
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Suppose $Y_i=g(X_i)+e_i$ with $E(e_i|X_i)=0$, $g(\cdot)$ being an unknown function and $X_i\in S=\{1,2,3,4\}$ with equal probability of taking each value. We want to estimate $g(x)$ using data $\{Y_i,... 1 vote 0 answers 133 views ### Derive an expression for the decision rule for a binary classification classifier I want to derive the decision rule for the local constant logistic regression: Consider the log-likelihood for the GLM (general linearised model) \begin{equation} l( \beta_{0}, \beta_{1})= \sum_{i=1}^{... 0 votes 0 answers 111 views ### Optimal grid for Nadaraya-Watson CV bandwidth selection Is there any rule of thumb or optimization technique for number of grid points for Kernel Regression? I am doing Nadaraya-Watson on 10 years data (2500 daily observations) of Swap rate. While ... 2 votes 1 answer 239 views ### Nadaraya Watson regression increasing bandwidth I'm working with the Nadaraya Watson estimator and read the book of Wand and Jones (Kernel Smoothing, 1995) for introduction. On page 117 (for those who have the book) there is written that with ... 0 votes 1 answer 412 views ### How can I implement univariate Nadaraya–Watson regression for prediction？ How can I implement univariate Nadaraya–Watson regression for prediction？ And what is the$x ,x_i$, and$y_i$? How can I select the$x ,x_i$, and$y_i$？ The sample for prediction and the shape of ... 0 votes 1 answer 103 views ### Multivariate plug-in bandwidth estimator local constant regression Has someone good references for multivariate plug-in bandwidth estimators in local constant regression? All I'm finding is for the univaraite case. And is there maybe already an implementation in R? ... 0 votes 1 answer 281 views ### Nadaraya Watson Bandwidth-Variance I'm working with the Nadaraya Watson estimator and calculate the optimal bandwidth h with leave one out cross validation. Now I'd like to get the variance of h (not the variance of the NW estimator).... 3 votes 0 answers 81 views ### Nonparametric Quantile Regression for AR(1)-ARCH(1) process I would like to estimate the conditional scale function$(\sigma_\tau(X_t))$in a QAR-QARCH model represented by: \begin{equation} Y_t = \mu_\tau(X_t) + \sigma_\tau(X_t)\epsilon_t,\, t = 1,2,\ldots \... 6 votes 2 answers 9k views ### How to choose appropriate bandwidth for kernel regression? I'm trying to understand how to choose an appropriate bandwidth for kernel regression. Note that this is NOT about kernel density estimation (unless someone can ... 7 votes 1 answer 3k views ### Nadaraya-Watson Optimal Bandwidth I am currently working on a statistical project where I need to estimate a conditional expectation$E[Y|X=x_i]$using the Nadaraya-Watson estimator. For doing that, I have the sample$(x_1,y_1),...,(...
Given a regression setting with covariates $X_{n \times m}$ and response $Y_{n \times p}$ where $p>1$, i.e the responses are vector-valued or multivariate, is there a Nadaraya-Watson estimator for ...