trend_columns

<p>the number of rows in the input data set.</p>

number_of_rows

<p>This function returns a matrix of linear and quadratic trends.</p>

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.

Ando Emerencia

trend_columns: Construct linear and quadratic trend columns

Description

Usage

Arguments

Value

Examples