Data

regression

time series

linear regression

time series forecasting

time series prediction

sarimax

missing imputation

prediction intervals

Machine learning algorithm for predicting and imputing time series. It can automatically set all the parameters needed, thus in the minimal configuration it only requires the target variable and the dependent variables if present. It can address large problems with hundreds or thousands of dependent variables and problems in which the number of dependent variables is greater than the number of observations. Moreover it can be used not only for time series but also for any other real valued target variable. The algorithm implemented includes a Bayesian stochastic search methodology for model selection and a robust estimation based on bootstrapping. 'rego' is fast because all the code is C++.

Davide Altomare

rego

Automatic Time Series Forecasting and Missing Value Imputation

David Loris

Data function

<p><code>Data</code> is a data.frame with 156 rows and 1 column containing the yearly number of airline passengers</p>

Format

Airline Passenger Dataset — Data

Airline Passenger Dataset

Data: Airline Passenger Dataset

Description

Usage

Arguments

Format