Fits sufficient dimension reduction models with optional covariance regularisation and information-theoretic structural dimension selection.
Usage
fit_risdr(
X,
y,
sdr_method = c("dr", "sir", "save", "phd"),
cov_method = c("sample", "ridge", "oas", "lw", "mec"),
stabilize = TRUE,
stabilization = c("eigenfloor", "ridge", "nearest_pd"),
nslices = 6,
d = NULL,
d_max = 10,
selector = c("cicomp", "icomp", "bic", "caic", "aic"),
standardize = TRUE,
complexity = c("C1", "C1F"),
cov_args = list(),
stabilization_args = list(),
sdr_args = list(),
...
)Arguments
- X
Numeric predictor matrix or data frame.
- y
Numeric continuous response vector.
- sdr_method
SDR method: "dr", "sir", "save", or "phd".
- cov_method
Covariance estimator: "sample", "ridge", "oas", "lw", or "mec".
- stabilize
Logical. If TRUE, stabilises the estimated covariance matrix.
- stabilization
Stabilisation method.
- nslices
Number of slices for inverse regression methods.
- d
Optional structural dimension. If NULL, selected by criterion.
- d_max
Maximum candidate structural dimension.
- selector
Criterion for selecting d.
- standardize
Logical. If TRUE, column-standardises X before covariance estimation.
- complexity
Complexity measure for ICOMP: "C1" or "C1F".
- cov_args
Named list of arguments for the selected covariance estimator.
- stabilization_args
Named list of arguments for covariance stabilisation.
- sdr_args
Named list of arguments for the selected SDR kernel.
- ...
Backward-compatible component arguments. New code should use the three explicit argument lists.
Examples
simulated <- simulate_risdr_data(
n = 60,
p = 6,
d = 2,
seed = 2026
)
fit <- fit_risdr(
X = simulated$X,
y = simulated$y,
sdr_method = "sir",
cov_method = "oas",
nslices = 4,
d = 1,
d_max = 3
)
fit
#> Regularised and Information-Theoretic SDR fit
#> --------------------------------------------------
#> SDR method : SIR
#> Covariance : OAS
#> Stabilised : TRUE
#> Stabilisation : eigenfloor
#> Selected d : 1
#> Selector : CICOMP
#> Number of slices : 4
#> Observations : 60
#> Predictors : 6