COVID

<p>A <code>ts</code> object that contains the daily confirmed new COVID-19 cases
in Germany (in thousands of cases) from June 2021 to November 2021.
The object contains 183 observations. The time series object is created 
as a time series object with frequency 7, i.e. the time unit is in calendar 
weeks of the year 2021 and not in years.</p>

datasets

Various methods for the identification of trend and seasonal
components in time series (TS) are provided. Among them is a data-driven locally
weighted regression approach with automatically selected bandwidth for
equidistant short-memory time series. The approach is a
combination / extension of the algorithms by
Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y., Gries, T.,
and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief
description of this new method is provided in the package documentation.
Furthermore, the package allows its users to apply the base model of the
Berlin procedure, version 4.1, as described in Speth (2004) <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>.
Permission to include this procedure was kindly provided by the Federal
Statistical Office of Germany.

Dominik Schulz

deseats

Data-Driven Locally Weighted Regression for Trend and
Seasonality in TS

Yuanhua Feng

COVID function

<p>An object of class <code>ts</code> of length 183.</p>

COVID: Daily Confirmed New COVID-19 Cases in Germany

Description

Usage

Arguments

Format