Nothing
eegsmooth <-
function(voltage, space = NULL, time = NULL, nknots = NULL,
rparm = NULL, lambdas = NULL, skip.iter = TRUE,
se.fit = FALSE, rseed = 1234){
###### Spatial and/or temporal smoothing of EEG data
###### Nathaniel E. Helwig (helwig@umn.edu)
###### Last modified: Mat 23, 2018
### check voltage
voltage <- as.matrix(voltage)
nv <- nrow(voltage)
if(ncol(voltage)!=1L){stop("Input 'voltage' must be column vector.")}
### check and fit model
if(is.null(space[1]) & is.null(time[1])){
stop("You must input either 'space' or 'time' to smooth.")
} else if(is.null(space[1])){
# initial checks
time <- as.matrix(time)
if(ncol(time)!=1L){stop("Input 'time' must be column vector.")}
if(nv!=nrow(time)){stop("Inputs 'voltage' and 'time' must have same number of rows.")}
# check knots and rparm
if(is.null(nknots)){nknots <- 30L} else {nknots <- as.integer(nknots[1])}
if(is.null(rparm)){rparm <- 0.001}
# fit model
eegmod <- bigspline(time,voltage,nknots=nknots,rparm=rparm,
lambdas=lambdas,se.fit=se.fit,rseed=rseed)
} else if(is.null(time[1])){
# initial checks
space <- as.matrix(space,rownames=0)
if(ncol(space)!=3L){stop("Input 'space' must be 3-column matrix of spatial coordinates.")}
if(nv!=nrow(space)){stop("Inputs 'voltage' and 'space' must have same number of rows.")}
# check knots and rparm
if(is.null(nknots)){nknots <- 100L} else {nknots <- as.integer(nknots[1])}
if(is.null(rparm)){rparm <- 0.1}
# fit model
eegmod <- bigtps(space,c(voltage),nknots=nknots,rparm=rparm,
lambdas=lambdas,se.fit=se.fit,rseed=rseed)
} else {
# initial checks
time <- as.matrix(time)
if(ncol(time)!=1L){stop("Input 'time' must be column vector.")}
if(nv!=nrow(time)){stop("Inputs 'voltage' and 'time' must have same number of rows.")}
space <- as.matrix(space)
if(ncol(space)!=3L){stop("Input 'space' must be 3-column matrix of spatial coordinates.")}
if(nv!=nrow(space)){stop("Inputs 'voltage' and 'space' must have same number of rows.")}
# check knots and rparm
if(is.null(nknots)){nknots <- 500L} else {nknots <- as.integer(nknots[1])}
if(is.null(rparm)){rparm <- list(space=0.1,time=0.001)}
# fit model
type <- list(space="tps",time="cub")
eegmod <- bigssa(voltage~space*time,nknots=nknots,type=type,rparm=rparm,
lambdas=lambdas,skip.iter=skip.iter,se.fit=se.fit,rseed=rseed)
} # end if(is.null(space[1]) & is.null(time[1]))
eegmod
}
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