chanInterp: Spherical spline interpolation

In tdeenes/eegR: Analyze EEG Signals

Description

chanInterp performs spherical spline interpolation. It can impute bad channels (i.e. channels with missing values) or interpolate to artbitrary positions on the scalp.

Usage

chanInterp(
  dat,
  ch_pos,
  interp_pos = NULL,
  maxNA = 0.3,
  m = 4L,
  N = 7L,
  lambda = 1e-10,
  type = c("voltage", "laplacian", "scd"),
  alarm_tolerance = 0.01,
  error_on_alarm = TRUE
)

Arguments

dat	a numeric vector, matrix, data.frame or array with named dimnames
ch_pos	channel (electrode) positions; should be a matrix or data.frame with the following column names (order is not important): "theta", "phi" (spherical coordinates), or "x", "y", "z" (cartesian coordinates)
interp_pos	interpolation positions, if they differ from ch_pos; should be in the same format as ch_pos (default: NULL)
maxNA	numeric value given as ratio (0 < maxNA < 1) or integer (maxNA >= 1 ); it determines the maximum ratio or number of non-missing channels in a time sample. If exceeded, no interpolation occurs in the given time sample.
m	integer value (default: 4); the flexibility of the spline
N	integer value (default: 7); number of terms in the Legendre polynomial. You should probably increase it (even up to 100L) for realistic (i.e. non-spherical) or high-density electrode arrangements.
lambda	numeric value (default: 1e-10); smoothing factor
type	character value, do not use yet
alarm_tolerance	numeric value (default: 1e-2); if the maximal absolute interpolation error at any time sample exceeds this limit, a message is shown or an error is thrown depending on error_on_alarm. If set to NULL, no check is performed.
error_on_alarm	defaults to TRUE, see alarm_tolerance

Value

An object having the same attributes as dat

tdeenes/eegR documentation built on April 19, 2021, 4:17 p.m.