# R/convertMV.R In PartialNetwork: Estimating Peer Effects Using Partial Network Data

#### Documented in mat.to.vecvec.to.mat

```#' @title Creating objects for network models
#' @description  `vec.to.mat` creates a list of square matrices from a given vector.
#' The elements of the generated matrices are taken from the vector and placed column-wise (ie. the first column is filled up before filling the second column) and from the first matrix of the list to the last matrix of the list.
#' The diagonal of the generated matrices are zeros.
#' `mat.to.vec` creates a vector from a given list of square matrices .
#' The elements of the generated vector are taken from column-wise and from the first matrix of the list to the last matrix of the list, while dropping the diagonal entry.
#' `norm.network` row-normalizes matrices in a given list.
#' @param u numeric vector to convert.
#' @param W matrix or list of matrices to convert.
#' @param N vector of sub-network sizes  such that `length(u) == sum(N*(N - 1))`.
#' @param normalise Boolean takes `TRUE` if the returned matrices should be row-normalized and `FALSE` otherwise.
#' @param ceiled Boolean takes `TRUE` if the given matrices should be ceiled before conversion and `FALSE` otherwise.
#' @param byrow Boolean takes `TRUE` is entries in the matrices should be taken by row and `FALSE` if they should be taken by column.
#' @return a vector of size `sum(N*(N - 1))` or list of `length(N)` square matrices. The sizes of the matrices are `N[1], N[2], ...`
#' @examples
#' # Generate a list of adjacency matrices
#' ## sub-network size
#' N <- c(250, 370, 120)
#' ## rate of friendship
#' p <- c(.2, .15, .18)
#' ## network data
#' u <- unlist(lapply(1: 3, function(x) rbinom(N[x]*(N[x] - 1), 1, p[x])))
#' W <- vec.to.mat(u, N)
#'
#' # Convert G into a list of row-normalized matrices
#' G <- norm.network(W)
#'
#' # recover u
#' v <- mat.to.vec(G, ceiled = TRUE)
#' all.equal(u, v)
#' @seealso
#' @export
vec.to.mat <- function(u, N, normalise = FALSE, byrow = FALSE) {
M        <- length(N)
stopifnot(length(u) == sum(N*(N - 1)))
out      <- NULL
if (normalise) {
out    <- frVtoMnorm(u, N, M)
} else {
out    <- frVtoM(u, N, M)
}

if(byrow) {
out    <- lapply(out, t)
}

out
}

#' @rdname vec.to.mat
#' @export
mat.to.vec <- function(W, ceiled = FALSE, byrow = FALSE) {
if (!is.list(W)) {
if (is.matrix(W)) {
W    <- list(W)
} else {
stop("W is neither a matrix nor a list")
}
}

M        <- length(W)
N        <- unlist(lapply(W, nrow))

out      <- W
if(byrow) {
out    <- lapply(W, t)
}
if (ceiled) {
out    <- frMceiltoV(out, N, M)
} else {
out    <- frMtoV(out, N, M)
}

out
}
```

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PartialNetwork documentation built on May 29, 2024, 10:08 a.m.