# R/seriestotpm.R In rinform: An R Wrapper of the 'Inform' C Library for Information Analysis of Complex Systems

#### Documented in series_to_tpm

```################################################################################
# Use of this source code is governed by a MIT license that can be found in the
################################################################################

################################################################################
#' 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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rinform documentation built on April 1, 2018, 12:12 p.m.