z.labels

This dataset gives the labelled activities recorded during the time period of observations given in the data
object <code>z.acc</code>.

datasets

Fitting models for, and simulation of, trend locally stationary
wavelet (TLSW) time series models, which take account of time-varying
trend and dependence structure in a univariate time series. The TLSW model,
and its estimation, is described in McGonigle, Killick and Nunes (2022a)
<doi:10.1111/jtsa.12643>, (2022b) <doi:10.1214/22-EJS2044>. Further information regarding the use of the package, along with detailed examples, can be found in McGonigle, Killick and Nunes (2025) <doi:10.18637/jss.v115.i10>. New users will
likely want to start with the TLSW function.

Euan T. McGonigle

TrendLSW

Wavelet Methods for Analysing Locally Stationary Time Series

Rebecca Killick

Matthew Nunes

z.labels function

A data frame with 6 rows and 3 variables:<dl>
 <dt>activity</dt>
<dd>The activity recorded, either <code>"downstairs"</code> or <code>"upstairs"</code>, corresponding to walking downstairs and upstairs respectively.</dd> <dt>start</dt>
<dd>the starting time of the activity.</dd> <dt>end</dt>
<dd>the ending time of the activity.</dd> 
</dl>

Format

This dataset gives the labelled activities recorded during the time period of observations given in the data
object <code>z.acc</code>.

Activity Labels for Human Activity Monitoring — z.labels

A data frame with 6 rows and 3 variables:<dl>
 <dt>activity</dt>
<dd>The activity recorded, either <code>"downstairs"</code> or <code>"upstairs"</code>, corresponding to walking downstairs and upstairs respectively.</dd>

 <dt>start</dt>
<dd>the starting time of the activity.</dd>

 <dt>end</dt>
<dd>the ending time of the activity.</dd>

 
</dl>

z.labels: Activity Labels for Human Activity Monitoring

Description

Usage

Arguments

Format

References

See Also