index.spatial.laggedCrosCor: Lagged Spatiotemporal Cross-Correlations

In SantanderMetGroup/VALUE: Climate data validation in the framework of the COST action VALUE

Lagged Spatiotemporal Cross-Correlations

Description

Function to compute the pairwise lagged cross-correlations for a set of grid points/stations.

Usage

index.spatial.laggedCrosCor(
  tsl,
  dates = NULL,
  lag = 1,
  type = "pearson",
  use = "pairwise.complete.obs",
  parallel = FALSE,
  max.ncores = 16,
  ncores = NULL
)

Arguments

tsl	A list of vectors (one for each gridpoint/station) containing the data
dates	A character (or POSIXct) vector following the format “YYYY-MM-DD” (i.e., format = "%Y-%m-%d" as in strptime). Note that, if dates are not provided, data will be considered consecutive.
lag	Time lag. 1 by default.
type	Correlation type: "pearson" or "spearman"
use	Check ?cor. "pairwise.complete.obs" (default) ignores uses all available info for each column pair.
parallel	Use parallel computation.
max.ncores	Maximum number of cores for parallel computing.
ncores	Number of threads for parallel computation. Default to ncores - 1.

Value

index.code matrix

Author(s)

M.N. Legasa

M. N. Legasa

SantanderMetGroup/VALUE documentation built on July 8, 2023, 7:03 a.m.