pic.calc {WASP}

Calculate PIC

Description

Calculate PIC

Usage

pic.calc(
  X,
  Y,
  Z,
  mode,
  wf,
  J,
  method = "dwt",
  pad = "zero",
  boundary = "periodic",
  cov.opt = "auto",
  flag = "biased",
  detrend = F
)

Arguments

X

A vector of response.

Y

A matrix of new predictors.

Z

A matrix of pre-existing predictors that could be NULL if no prior predictors exist.

mode

A mode of variance transfomration, i.e., MRA, MODWT, or AT

wf

Wavelet family

J

The maximum decomposition level

method

Either "dwt" or "modwt" of MRA.

pad

The method used for extend data to dyadic size. Use "per", "zero", or "sym".

boundary

Character string specifying the boundary condition. If boundary=="periodic" the default, then the vector you decompose is assumed to be periodic on its defined interval, if boundary=="reflection", the vector beyond its boundaries is assumed to be a symmetric reflection of itself.

cov.opt

Options of Covariance matrix sign. Use "pos", "neg", or "auto".

flag

Biased or Unbiased variance transformation.

detrend

Detrend the input time series or just center, default (F).

Value

A list of 2 elements: the partial mutual information (pmi), and partial informational correlation (pic).

References

Sharma, A., Mehrotra, R., 2014. An information theoretic alternative to model a natural system using observational information alone. Water Resources Research, 50(1): 650-660.

Galelli S., Humphrey G.B., Maier H.R., Castelletti A., Dandy G.C. and Gibbs M.S. (2014) An evaluation framework for input variable selection algorithms for environmental data-driven models, Environmental Modelling and Software, 62, 33-51, DOI: 10.1016/j.envsoft.2014.08.015.