A Multivariate Approach to Time Series Forecasting of Copper Prices with the Help of Multiple Imputation by Chained Equations and Multivariate Adaptive Regression Splines.
Fernando Sánchez LasherasJavier Gracia RodríguezPaulino José García NietoEsperanza García GonzaloGregorio Fidalgo ValverdePublished in: SOCO (2020)
Keyphrases
- multivariate adaptive regression splines
- multiple imputation
- missing data
- statistical databases
- incomplete data
- support vector regression
- missing values
- mathematical model
- regression model
- artificial neural networks
- thin film
- differential equations
- long run
- expectation maximization
- magnetic recording
- neuro fuzzy
- multivariate time series
- pattern recognition
- data mining
- decision trees
- dynamic pricing
- electricity markets
- image segmentation
- neural network
- input data
- machine learning algorithms
- model selection