cv.fastmds: Repeated Cross-Validation Penalized Restricted Multidimensional Scaling Function

Description

cv.fastmds performs repeated cross-validation for a penalized restricted multidimensional scaling model.

Usage

cv.fastmds(
  delta,
  w = NULL,
  p = 2,
  q = NULL,
  b = NULL,
  lambda = 0,
  alpha = 1,
  grouped = FALSE,
  NFOLDS = 10,
  NREPEATS = 30,
  MAXITER = 1024,
  FCRIT = 1e-08,
  ZCRIT = 1e-06,
  error.check = FALSE,
  echo = FALSE
)

Value

mserrors mean squared errors for different values of lambda.

stderrors standard errors for mean squared errors.

varnames labels of independent row variables.

coefficients list with final h by p matrices with regression coefficients (lambda order).

lambda sorted regularization penalty parameters.

alpha elastic-net parameter (default = 1.0: lasso only).

grouped boolean for lasso penalty (default = FALSE: ordinary lasso).

Arguments

delta: an n by n symmatric and hollow matrix containing dissimilarities.
w: an identical sized matrix containing nonnegative weights (all ones when omitted).
p: dimensionality (default = 2).
q: independent variables (n by h).
b: initial regression coefficients (h by p).
lambda: regularization penalty parameter(s) (default = 0.0: no penalty).
alpha: elastic-net parameter (default = 1.0: lasso only).
grouped: boolean for lasso penalty (default = FALSE: ordinary lasso).
NFOLDS: number of folds for the k-fold cross-validation.
NREPEATS: number of repeats for the repeated k-fold cross-validation.
MAXITER: maximum number of iterations (default = 1024).
FCRIT: relative convergence criterion function value (default = 0.00000001).
ZCRIT: absolute convergence criterion coordinates (default = 0.000001).
error.check: extensive check validity input parameters (default = FALSE).
echo: print intermediate algorithm results (default = FALSE).

References

de Leeuw, J., and Heiser, W. J. (1980). Multidimensional scaling with restrictions on the configuration. In P.R. Krishnaiah (Ed.), Multivariate analysis (Vol. 5, pp. 501–522). Amsterdam, The Netherlands: North-Holland Publishing Company.

Heiser,W. J. (1987a). Joint ordination of species and sites: The unfolding technique. In P. Legendre and L. Legendre (Eds.), Developments in numerical ecology (pp. 189–221). Berlin, Heidelberg: Springer-Verlag.

Busing, F.M.T.A. (2010). Advances in multidimensional unfolding. Unpublished doctoral dissertation, Leiden University, Leiden, the Netherlands.