returns.alv

<p>The (log-) returns of the shares of the German insurance company Allianz SE
from 2007-01-02 to 2010-12-30 aggregated to 5-minute observations. The data
is adjusted to matrix form for direct use with the <code>DCSmooth</code>-functions.</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 

returns.alv function

<p>A numeric matrix with 1016 rows representing the days and 101 columns
representing the intraday time points.</p>

returns.alv: Returns of Allianz SE

Description

Usage

Arguments

Format