## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

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

sim <- simulate_risdr_data(
  n = 120,
  p = 30,
  d = 2,
  rho = 0.8,
  sigma = 1,
  model = "linear_quadratic",
  beta_type = "coordinate",
  seed = 9201
)

dim(sim$X)
crossprod(sim$beta)

## -----------------------------------------------------------------------------
one <- run_one_simulation(
  n = 100,
  p = 20,
  d = 2,
  rho = 0.6,
  sigma = 1,
  model = "linear_quadratic",
  sdr_method = "dr",
  cov_method = "oas",
  nslices = 6,
  d_max = 5,
  seed = 9202
)

one

## -----------------------------------------------------------------------------
small_study <- run_risdr_simulation(
  R = 2,
  rho_values = c(0.3, 0.8),
  methods = c("sir", "dr"),
  cov_methods = c("ridge", "oas"),
  n = 80,
  p = 15,
  d = 2,
  nslices = 5,
  d_max = 4,
  seed = 9203
)

summarise_simulation(small_study)

## -----------------------------------------------------------------------------
simulation_a <- utils::read.csv(system.file(
  "extdata",
  "simulation",
  "simulation_A_final_covariance_DR_summary_tidy.csv",
  package = "risdr"
))

aggregate(
  cbind(
    mean_subspace_distance,
    mean_RMSE,
    mean_condition_number,
    mean_runtime_seconds
  ) ~ cov_method,
  data = simulation_a,
  FUN = mean
)

## -----------------------------------------------------------------------------
ranking_b1 <- utils::read.csv(system.file(
  "extdata",
  "simulation",
  "simulation_B1_overall_ranking.csv",
  package = "risdr"
))

ranking_b1[order(ranking_b1$avg_subspace_distance), ]

## -----------------------------------------------------------------------------
ranking_b2 <- utils::read.csv(system.file(
  "extdata",
  "simulation",
  "simulation_B2_overall_ranking.csv",
  package = "risdr"
))

ranking_b2[
  order(ranking_b2$avg_dimension_recovery_rate, decreasing = TRUE),
]