| Type: | Package |
| Title: | Iterative Hard Thresholding Extensions to Cyclops |
| Version: | 1.0.3 |
| Date: | 2025-7-21 |
| Maintainer: | Marc A. Suchard <msuchard@ucla.edu> |
| Description: | Fits large-scale regression models with a penalty that restricts the maximum number of non-zero regression coefficients to a prespecified value. While Chu et al (2020) <doi:10.1093/gigascience/giaa044> describe the basic algorithm, this package uses Cyclops for an efficient implementation. |
| License: | Apache License 2.0 |
| Depends: | R (≥ 3.2.2), Cyclops (≥ 1.3.0) |
| Imports: | ParallelLogger |
| Suggests: | testthat, knitr, rmarkdown |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-07-21 18:55:07 UTC; msuchard |
| Author: | Marc A. Suchard [aut, cre], Patrick Ryan [aut], Observational Health Data Sciences and Informatics [cph] |
| Repository: | CRAN |
| Date/Publication: | 2025-07-21 19:11:35 UTC |
Create a fastIHT Cyclops prior object
Description
createFastIhtPrior creates a fastIHT Cyclops prior object for use with fitCyclopsModel.
Usage
createFastIhtPrior(
K,
penalty = 0,
exclude = c(),
forceIntercept = FALSE,
fitBestSubset = FALSE,
initialRidgeVariance = 10000,
tolerance = 1e-08,
maxIterations = 10000,
threshold = 1e-06
)
Arguments
K |
Maximum # of non-zero covariates |
penalty |
Specifies the IHT penalty |
exclude |
A vector of numbers or covariateId names to exclude from prior |
forceIntercept |
Logical: Force intercept coefficient into regularization |
fitBestSubset |
Logical: Fit final subset with no regularization |
initialRidgeVariance |
Numeric: variance used for algorithm initiation |
tolerance |
Numeric: maximum abs change in coefficient estimates from successive iterations to achieve convergence |
maxIterations |
Numeric: maximum iterations to achieve convergence |
threshold |
Numeric: absolute threshold at which to force coefficient to 0 |
Value
An IHT Cyclops prior object of class inheriting from
"cyclopsPrior" for use with fitCyclopsModel.
Examples
nobs = 500; ncovs = 100
prior <- createFastIhtPrior(K = 3, penalty = log(ncovs), initialRidgeVariance = 1 / log(ncovs))
Create an IHT Cyclops prior object
Description
createIhtPrior creates an IHT Cyclops prior object for use with fitCyclopsModel.
Usage
createIhtPrior(
K,
penalty = "bic",
exclude = c(),
forceIntercept = FALSE,
fitBestSubset = FALSE,
initialRidgeVariance = 0.1,
tolerance = 1e-08,
maxIterations = 10000,
threshold = 1e-06,
delta = 0
)
Arguments
K |
Maximum # of non-zero covariates |
penalty |
Specifies the IHT penalty; possible values are 'BIC' or 'AIC' or a numeric value |
exclude |
A vector of numbers or covariateId names to exclude from prior |
forceIntercept |
Logical: Force intercept coefficient into regularization |
fitBestSubset |
Logical: Fit final subset with no regularization |
initialRidgeVariance |
Numeric: variance used for algorithm initiation |
tolerance |
Numeric: maximum abs change in coefficient estimates from successive iterations to achieve convergence |
maxIterations |
Numeric: maximum iterations to achieve convergence |
threshold |
Numeric: absolute threshold at which to force coefficient to 0 |
delta |
Numeric: change from 2 in ridge norm dimension |
Value
An IHT Cyclops prior object of class inheriting from
"cyclopsPrior" for use with fitCyclopsModel.
Examples
prior <- createIhtPrior(K = 10)