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# Copyright 2001-10 by Roger Bivand, Markus Reder and Werner Mueller, 2015 Martin Gubri
#
nb2mat <- function(neighbours, glist=NULL, style="W", zero.policy=NULL)
{
if (is.null(zero.policy))
zero.policy <- get("zeroPolicy", envir = .spdepOptions)
stopifnot(is.logical(zero.policy))
if(!inherits(neighbours, "nb")) stop("Not a neighbours list")
listw <- nb2listw(neighbours, glist=glist, style=style,
zero.policy=zero.policy)
res <- listw2mat(listw)
attr(res, "call") <- match.call()
res
}
listw2mat <- function(listw) {
n <- length(listw$neighbours)
if (n < 1) stop("non-positive number of entities")
cardnb <- card(listw$neighbours)
if (any(is.na(unlist(listw$weights))))
stop ("NAs in general weights list")
res <- matrix(0, nrow=n, ncol=n)
for (i in 1:n)
if (cardnb[i] > 0)
res[i, listw$neighbours[[i]]] <- listw$weights[[i]]
if (!is.null(attr(listw, "region.id")))
row.names(res) <- attr(listw, "region.id")
res
}
invIrM <- function(neighbours, rho, glist=NULL, style="W", method="solve",
feasible=NULL) {
if(class(neighbours) != "nb") stop("Not a neighbours list")
invIrW(nb2listw(neighbours, glist=glist, style=style), rho=rho,
method=method, feasible=feasible)
}
invIrW <- function(x, rho, method="solve", feasible=NULL) {
if(inherits(x, "listw")) {
n <- length(x$neighbours)
V <- listw2mat(x)
} else if (inherits(x, "Matrix") || inherits(x, "matrix")) {
if (method == "chol" && all(t(x) == x))
stop("No Cholesky method for matrix or sparse matrix object")
n <- dim(x)[1]
V <- x
} else stop("Not a weights list or a Sparse Matrix")
if (is.null(feasible) || (is.logical(feasible) && !feasible)) {
e <- eigen(V, only.values = TRUE)$values
if (is.complex(e)) feasible <- 1/(range(Re(e)))
else feasible <- 1/(range(e))
if (rho <= feasible[1] || rho >= feasible[2])
stop(paste("Rho", rho, "outside feasible range:",
paste(feasible, collapse=":")))
}
if (method == "chol"){
if (x$style %in% c("W", "S") && !(can.be.simmed(x)))
stop("Cholesky method requires symmetric weights")
if (x$style %in% c("B", "C", "U") &&
!(is.symmetric.glist(x$neighbours, x$weights)))
stop("Cholesky method requires symmetric weights")
if (x$style %in% c("W", "S")) {
V <- listw2mat(listw2U(similar.listw(x)))
}
mat <- diag(n) - rho * V
res <- chol2inv(chol(mat))
} else if (method == "solve") {
mat <- diag(n) - rho * V
res <- solve(mat)
} else stop("unknown method")
attr(res, "call") <- match.call()
res
}
powerWeights <- function(W, rho, order=250, X, tol=.Machine$double.eps^(3/5)) {
timings <- list()
.ptime_start <- proc.time()
n <- dim(W)[1]
dX <- dim(X)
if (dX[1] == n) side <- "R"
else if (dX[2] == n) side <- "L"
else stop("W and X non-conformant")
aW <- rho*W
if (side == "R") last <- aW %*% X
else last <- X %*% aW
acc <- X + last
conv <- FALSE
iter <- 1
series <- numeric(order)
while (iter < order) {
if (side == "R") {
last <- aW %*% last
acc <- acc + last
} else {
last <- last %*% aW
acc <- acc + last
}
# abs() added 2017-02-15, bug spotted by Yongwan Chun
series[iter] <- mean(abs(as(last, "matrix")))
if (series[iter] < tol) {
conv <- TRUE
break
}
iter <- iter+1
}
if (!conv) warning("not converged within order iterations")
timings[["make_power_sum"]] <- proc.time() - .ptime_start
attr(acc, "internal") <- list(series=series, order=order,
tol=tol, iter=iter, conv=conv)
attr(acc, "timings") <- do.call("rbind", timings)[, c(1, 3)]
acc
}
mat2listw <- function(x, row.names=NULL, style="M") {
if (!(is.matrix(x) || is(x, "sparseMatrix"))) stop("x is not a matrix")
n <- nrow(x)
if (n < 1) stop("non-positive number of entities")
m <- ncol(x)
if (n != m) stop("x must be a square matrix")
if (any(x < 0)) stop("values in x cannot be negative")
if (any(is.na(x))) stop("NA values in x not allowed")
if (!is.null(row.names)) {
if(length(row.names) != n)
stop("row.names wrong length")
if (length(unique(row.names)) != length(row.names))
stop("non-unique row.names given")
}
if (is.null(row.names)) {
if (!is.null(row.names(x))) {
row.names <- row.names(x)
} else {
row.names <- as.character(1:n)
}
}
# style <- "M"
if (is(x, "sparseMatrix")) {
xC <- as(x, "dgCMatrix")
i <- slot(xC, "i")+1
p <- slot(xC, "p")
dp <- diff(p)
rp <- rep(seq_along(dp), dp)
df0 <- data.frame(from=i, to=rp, weights=slot(xC, "x"))
o <- order(df0$from, df0$to)
df <- df0[o,]
class(df) <- c(class(df), "spatial.neighbour")
attr(df, "region.id") <- row.names
attr(df, "n") <- dim(xC)[1]
res <- sn2listw(df)
neighbours <- res$neighbours
weights <- res$weights
} else {
neighbours <- vector(mode="list", length=n)
weights <- vector(mode="list", length=n)
for (i in 1:n) {
nbs <- which(x[i,] > 0.0)
if (length(nbs) > 0) {
neighbours[[i]] <- nbs
weights[[i]] <- as.double(x[i, nbs]) # Laurajean Lewis
} else {
neighbours[[i]] <- 0L
}
}
}
attr(weights, "mode") <- "unknown" # Brian Rubineau
class(neighbours) <- "nb"
attr(neighbours, "region.id") <- row.names
attr(neighbours, "call") <- NA
attr(neighbours, "sym") <- is.symmetric.nb(neighbours,
verbose=FALSE, force=TRUE)
res <- list(style=style, neighbours=neighbours, weights=weights)
class(res) <- c("listw", "nb")
attr(res, "region.id") <- attr(neighbours, "region.id")
attr(res, "call") <- match.call()
if (style != "M") {
res <- nb2listw(res$neighbours, glist=res$weights, style=style,
zero.policy=TRUE)
}
res
}
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