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################################################################################
# Copyright 2017-2018 Gabriele Valentini, Douglas G. Moore. All rights reserved.
# Use of this source code is governed by a MIT license that can be found in the
# LICENSE file.
################################################################################
################################################################################
#' Time Series to TPM
#'
#' Estimate the one-time-step transition probability matrix `A` from a time
#' series. The element `A_{ji}` is the probability of transitioning to state
#' `j` in the next time step given the system is in state `i` (note the
#' column-major convention).
#'
#' @param series Vector or matrix specifying one or more time series.
#'
#' @return Matrix giving the corresponding transition probability matrix.
#'
#' @example inst/examples/ex_series_to_tpm.R
#'
#' @export
#'
#' @useDynLib rinform r_series_to_tpm_
################################################################################
series_to_tpm <- function(series) {
n <- 0
m <- 0
err <- 0
.check_series(series)
# Extract number of series and length
if (is.vector(series)) {
n <- 1
m <- length(series)
} else if (is.matrix(series)) {
n <- dim(series)[2]
m <- dim(series)[1]
}
# Compute the value of <b>
b <- max(2, max(series) + 1)
tpm <- rep(0.0, b * b)
x <- .C("r_series_to_tpm_",
series = as.integer(series),
n = as.integer(n),
m = as.integer(m),
b = as.integer(b),
tpm = as.double(tpm),
err = as.integer(err))
if (.check_inform_error(x$err) == 0) {
tpm <- x$tpm
dim(tpm) <- c(b, b)
}
tpm
}
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