one_lds_cv {ldsr}

One cross-validation run

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.