Nothing
lin_narpq_init <- function(y, W, p, Z = NULL) {
if ( min(W) < 0 ) {
stop('The adjacency matrix W contains negative values.')
}
if ( !is.null(Z) ) {
if ( min(Z) < 0 ) {
stop('The matrix of covariates Z contains negative values.')
}
Z <- model.matrix(~., as.data.frame(Z))
Z <- Z[1:dim(y)[2], -1, drop = FALSE]
}
y <- t(y)
W <- W / Rfast::rowsums(W)
W[ is.na(W) ] <- 0
dm <- dim(y) ; N <- dm[1] ; TT <- dm[2]
z <- W %*% y
wy <- NULL
for ( ti in (p + 1):TT ) wy <- rbind( wy, cbind(z[, (ti - 1):(ti - p)], y[, (ti - 1):(ti - p)], Z) )
wy <- cbind(1, wy)
XX <- crossprod(wy)
Xy <- Rfast::eachcol.apply(wy, as.vector( y[, -c(1:p)] ) )
x0 <- solve(XX, Xy)
x0[x0 < 0] <- 0.001
x0
}
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