WPSA: p-Wasserstein distance projections using simulated annealing

In WpProj: Linear p-Wasserstein Projections

p-Wasserstein distance projections using simulated annealing

Description

p-Wasserstein distance projections using simulated annealing

Usage

WPSA(
  X,
  Y = NULL,
  theta,
  power = 2,
  force = NULL,
  model.size = 3,
  nvars = NULL,
  maxit = 1,
  temps = 1000,
  max.time = 3600,
  const = NULL,
  proposal = proposal.fun,
  options = list(method = c("selection.variable", "scale", "projection"),
    transport.method = transport_options(), energy.distribution = "boltzman",
    cooling.schedule = "Geman-Geman", proposal.method = "covariance", epsilon = 0.05,
    OTmaxit = 100),
  display.progress = FALSE,
  parallel = NULL,
  calc.theta = TRUE,
  xtx = NULL,
  xty = NULL,
  ...
)

Arguments

X	Covariate vector
Y	Predictions
theta	Optional matrix of parameters for generating predictions
power	Power of the Wasserstein distance
force	Any covariates to force into the model?
model.size	Maximum number of coefficients
nvars	The number of variables to explore. Should be an integer vector of model sizes. Default is NULL which will explore all models from 1 to model.size.
maxit	Maximum number of iterations
temps	Number of temperatures
max.time	Maximum time in seconds to run
const	Maximum value for simulated annealing distance
proposal	Proposal function. There is a default method but can provide your own with parameters xty, cur, idx, force, d, method
options	Options for simulated annealing
display.progress	Whether to display solver progress. TRUE or FALSE. Default is FALSE.
parallel	A foreach::foreach() backend
calc.theta	Should the model save the linear coefficients? TRUE or FALSE. Default is TRUE
xtx	precomputed crossproduct crossprod(X,X)
xty	precomputed crossprod(X, Y)

Value

An object of class WpProj

WpProj documentation built on May 29, 2024, 7:55 a.m.