Sparse Multiple Index Modelsfor High-dimensional Nonparametric Forecasting
Nuwani Palihawadana (),
Rob Hyndman and
Xiaoqian Wang
No 16/24, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
Abstract:
Forecasting often involves high-dimensional predictors which have nonlinear relationships with theoutcome of interest. Nonparametric additive index models can capture these relationships, while addressing the curse of dimensionality. This paper introduces a new algorithm, Sparse Multiple Index (SMI) Modelling, tailored for estimating high-dimensional nonparametric/semi-parametric additive index models, while limiting the number of parameters to estimate, by optimising predictor selectionand predictor grouping. The SMI Modelling algorithm uses an iterative approach based on mixed integer programming to solve an L0-regularised nonlinear least squares optimisation problem withlinear constraints. We demonstrate the performance of the proposed algorithm through a simulation study, along with two empirical applications to forecast heat-related daily mortality and daily solarintensity.
Keywords: Additive Index Models; Variable Selection; Dimension Reduction; Predictor Grouping; Mixed Integer Programming (search for similar items in EconPapers)
Pages: Â 28
Date: 2024
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.monash.edu/business/ebs/research/publications/ebs/2024/wp16-2024.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:msh:ebswps:2024-16
Ordering information: This working paper can be ordered from
http://business.mona ... -business-statistics
Access Statistics for this paper
More papers in Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics PO Box 11E, Monash University, Victoria 3800, Australia. Contact information at EDIRC.
Bibliographic data for series maintained by Professor Xibin Zhang ().