y.norm1

<p>Example data for using the DCSmooth functions. Data resembles a single
  gaussian peak on the interval \([0,1] \times [0,1]\)
  with maximum at \((0.5, 0.5)\) and variance matrix \(0.1 \cdot
 {\bf I}\), where 
  \({\bf I}\) represents the \(2 \times 2\) identity matrix.</p>

datasets

Nonparametric smoothing techniques for data on a lattice and
functional time series. Smoothing is done via kernel regression or
local polynomial regression, a bandwidth selection procedure based on
an iterative plug-in algorithm is implemented. This package allows for
modeling a dependency structure of the error terms of the
nonparametric regression model.  Methods used in this paper are
described in Feng/Schaefer (2021)
<https://ideas.repec.org/p/pdn/ciepap/144.html>, Schaefer/Feng (2021)
<https://ideas.repec.org/p/pdn/ciepap/143.html>.

Bastian Schaefer

DCSmooth

Nonparametric Regression and Bandwidth Selection for Spatial
Models

Sebastian Letmathe

Yuanhua Feng 

y.norm1 function

<p>A numeric matrix with 101 rows and 101 columns.</p>

y.norm1: Single Gaussian Peak

Description

Usage

Arguments

Format