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

#### Documented in predictive_info

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

################################################################################
#' Predictive Information
#'
#' Compute the predictive information from a time series with history length
#' \code{kpast} and future length \code{kfuture}.
#'
#' @param series Vector or matrix specifying one or more time series.
#' @param kpast Integer giving the history length.
#' @param kfuture Integer giving the future length.
#' @param local Boolean specifying whether to compute the local predictive
#'        information.
#'
#' @return Numeric giving the average predictive information or a vector giving
#'         the local predictive information.
#'
#' @example inst/examples/ex_predictiveinfo.R
#'
#' @export
#'
#' @useDynLib rinform r_predictive_info_
#' @useDynLib rinform r_local_predictive_info_
################################################################################
predictive_info <- function(series, kpast, kfuture, local = FALSE) {
n   <- 0
m   <- 0
pi  <- 0
err <- 0

.check_series(series)
.check_history(kpast)
.check_history(kfuture)
.check_local(local)

# 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]
}

# Convert to integer vector suitable for C
xs <- as.integer(series)

# Compute the value of <b>
b <- max(2, max(xs) + 1)

if (!local) {
x <- .C("r_predictive_info_",
series  = xs,
n       = as.integer(n),
m       = as.integer(m),
b       = as.integer(b),
kpast   = as.integer(kpast),
kfuture = as.integer(kfuture),
rval    = as.double(pi),
err     = as.integer(err))

if (.check_inform_error(x\$err) == 0) {
pi <- x\$rval
}
} else {
pi <- rep(0, (m - kpast - kfuture + 1) * n)
x <- .C("r_local_predictive_info_",
series  = xs,
n       = as.integer(n),
m       = as.integer(m),
b       = as.integer(b),
kpast   = as.integer(kpast),
kfuture = as.integer(kfuture),
rval    = as.double(pi),
err     = as.integer(err))

if (.check_inform_error(x\$err) == 0) {
pi      <- x\$rval
dim(pi) <- c(m - kpast - kfuture + 1, n)
}
}

pi
}
```

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