one_lds_cv: One cross-validation run

In ldsr: Linear Dynamical System Reconstruction

Description

Make one prediction for one cross-validation run. This is a subroutine that is called by cvLDS, without any checks. You should not need to use this directly.

Usage

one_lds_cv(
  z,
  instPeriod,
  mu,
  y,
  u,
  v,
  method = "EM",
  num.restarts = 20,
  ub = NULL,
  lb = NULL,
  num.islands = 4,
  pop.per.island = 100,
  niter = 1000,
  tol = 1e-06,
  use.raw = FALSE
)

Arguments

z	A vector of left-out points, indexed according to the intrumental period
instPeriod	indices of the instrumental period in the whole record
mu	Mean of the observations
y	Catchment output, preprocessed from data
u	Input matrix for a single-model reconstruction, or a list of input matrices for an ensemble reconstruction.
v	Same as u.
method	By default this is "EM". There are experimental methods but you should not try.
num.restarts	The number of initial conditions to start the EM search; ignored if init is provided.
ub	Upper bounds, a vector whose length is the number of parameters
lb	Lower bounds
num.islands	Number of islands (if method is GA; experimental)
pop.per.island	Initial population per island (if method is GA; experimental)
niter	Maximum number of iterations, default 1000
tol	Tolerance for likelihood convergence, default 1e-5. Note that the log-likelihood is normalized by dividing by the number of observations.
use.raw	Whether performance metrics are calculated on the raw time series. Experimental; don't use.

Value

A vector of prediction.

ldsr documentation built on May 4, 2020, 5:06 p.m.