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smimodel  

Sparse Multiple Index Models for Nonparametric Forecasting
View on CRAN: Click here


Download and install smimodel package within the R console
Install from CRAN:
install.packages("smimodel")

Install from Github:
library("remotes")
install_github("cran/smimodel")

Install by package version:
library("remotes")
install_version("smimodel", "0.1.3")



Attach the package and use:
library("smimodel")
Maintained by
Nuwani Palihawadana
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-04-08
Latest Update: 2026-04-08
Description:
Implements a general algorithm for estimating Sparse Multiple Index (SMI) models for nonparametric forecasting and prediction. Estimation of SMI models requires the Gurobi mixed integer programming (MIP) solver via the gurobi R package. To use this functionality, the Gurobi Optimizer must be installed, and a valid license obtained and activated from <https://www.gurobi.com>. The gurobi R package must then be installed and configured following the instructions at <https://support.gurobi.com/hc/en-us/articles/14462206790033-How-do-I-install-Gurobi-for-R>. The package also includes functions for fitting nonparametric additive models with backward elimination, group-wise additive index models, and projection pursuit regression models as benchmark comparison methods. In addition, it provides tools for generating prediction intervals to quantify uncertainty in point forecasts produced by the SMI model and benchmark models, using the classical block bootstrap and a new method called conformal bootstrap, which integrates block bootstrap with split conformal prediction.
How to cite:
Nuwani Palihawadana (2026). smimodel: Sparse Multiple Index Models for Nonparametric Forecasting. R package version 0.1.3, https://cran.r-project.org/web/packages/smimodel. Accessed 09 Jun. 2026.
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