bookshop_orders

Individual orders of a Czech antiquarian bookshop from June 8, 2018 to December 20, 2018.
This dataset is analyzed in Tomanová and Holý (2021).

datasets

Estimation, forecasting, and simulation of generalized
autoregressive score (GAS) models of Creal, Koopman, and Lucas (2013)
<doi:10.1002/jae.1279> and Harvey (2013) <doi:10.1017/cbo9781139540933>.
Model specification allows for various data types and distributions,
different parametrizations, exogenous variables, joint and separate modeling
of exogenous variables and dynamics, higher score and autoregressive orders,
custom and unconditional initial values of time-varying parameters, fixed
and bounded values of coefficients, and missing values. Model estimation is
performed by the maximum likelihood method.

Vladimír Holý

gasmodel

Generalized Autoregressive Score Models

bookshop_orders function

A data frame with columns:<dl>
 <dt>id</dt>
<dd>ID of the order.</dd> <dt>datetime</dt>
<dd>Date and time of the order.</dd> <dt>quantity</dt>
<dd>Number of purchased books.</dd> <dt>duration</dt>
<dd>Number of minutes since the last order.</dd> <dt>duration_adj</dt>
<dd>Duration since the last order adjusted for diurnal pattern.</dd>
</dl>

Format

Antiquarian Bookshop Orders — bookshop_orders

A data frame with columns:<dl>
 <dt>id</dt>
<dd>ID of the order.</dd>

 <dt>datetime</dt>
<dd>Date and time of the order.</dd>

 <dt>quantity</dt>
<dd>Number of purchased books.</dd>

 <dt>duration</dt>
<dd>Number of minutes since the last order.</dd>

 <dt>duration_adj</dt>
<dd>Duration since the last order adjusted for diurnal pattern.</dd>


</dl>

bookshop_orders: Antiquarian Bookshop Orders

Description

Usage

Arguments

Format

References