## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 7,
  fig.height = 5
)

## -----------------------------------------------------------------------------
library(risdr)

sim <- simulate_risdr_data(
  n = 160,
  p = 20,
  d = 2,
  rho = 0.6,
  sigma = 0.7,
  model = "linear_quadratic",
  seed = 2026
)

## -----------------------------------------------------------------------------
str(sim[c("X", "y", "beta", "Sigma", "n", "p", "d")], max.level = 1)

## -----------------------------------------------------------------------------
fit <- fit_risdr(
  X = sim$X,
  y = sim$y,
  sdr_method = "dr",
  cov_method = "oas",
  nslices = 6,
  d_max = 6,
  selector = "cicomp",
  standardize = TRUE,
  stabilize = TRUE
)

fit
summary(fit)

## -----------------------------------------------------------------------------
fit$d_table
criterion_weights(fit$d_table, criterion = "CICOMP")

## -----------------------------------------------------------------------------
cv <- select_dimension_cv(
  X = sim$X,
  y = sim$y,
  sdr_method = "dr",
  cov_method = "oas",
  d_max = 5,
  v = 5,
  nslices = 6,
  metric = "RMSE",
  seed = 2026
)

cv$selected_d
cv$cv_table

## -----------------------------------------------------------------------------
predicted <- predict(fit, sim$X[1:12, , drop = FALSE])
evaluate_prediction(
  y_true = sim$y[1:12],
  y_pred = predicted,
  d = fit$d
)

## -----------------------------------------------------------------------------
fit_ridge <- fit_risdr(
  X = sim$X,
  y = sim$y,
  sdr_method = "sir",
  cov_method = "ridge",
  d = 2,
  d_max = 5,
  cov_args = list(lambda = 0.15),
  stabilization_args = list(eps = 1e-7),
  sdr_args = list(slice_type = "quantile")
)

## ----fig.show="hold"----------------------------------------------------------
plot_scree(fit, n_eigen = 10)
plot_sufficient(fit, direction = 1)
plot_dimension_selection(fit)