day_dummies

the number of rows in the input data set.

number_of_rows

the number of measurements per day in the input data set.

measurements_per_day

This function returns either <code>NULL</code> (if <code>measurements_per_day</code> is 0) or a matrix of weekday dummy variables specified number of rows and measurements per day. In the latter case, we return a matrix of six columns.

Automatically find the best vector autoregression
models and networks for a given time series data set. 'AutovarCore'
evaluates eight kinds of models: models with and without log
transforming the data, lag 1 and lag 2 models, and models with and
without weekday dummy variables. For each of these 8 model configurations,
'AutovarCore' evaluates all possible combinations for including
outlier dummies (at 2.5x the standard deviation of the residuals)
and retains the best model. Model evaluation includes the Eigenvalue
stability test and a configurable set of residual tests. These eight
models are further reduced to four models because 'AutovarCore'
determines whether adding weekday dummies improves the model fit.

day_dummies: Calculate weekday dummy variables

Description

Usage

Arguments

Value

Examples