diff options
| -rw-r--r-- | R/nonparam.R | 26 | ||||
| -rw-r--r-- | man/impulseest.Rd | 15 | ||||
| -rw-r--r-- | man/plot.impulseest.Rd | 3 | ||||
| -rw-r--r-- | man/step.Rd | 7 |
4 files changed, 43 insertions, 8 deletions
diff --git a/R/nonparam.R b/R/nonparam.R index 1450110..73c76f7 100644 --- a/R/nonparam.R +++ b/R/nonparam.R @@ -1,7 +1,7 @@ -#' Estimate Impulse Response Models +#' Estimate Impulse Response Coefficients #' -#' \code{impulseest} is used to estimate impulse response models in the -#' given data +#' \code{impulseest} is used to estimate impulse response coefficients from +#' the data #' #' @param data an object of class \code{idframe} #' @param M Order of the FIR Model (Default:\code{30}) @@ -12,6 +12,15 @@ #' @param lambda The value of the regularization parameter. Valid only if #' \code{regul=TRUE}. (Default:\code{1}) #' +#' @details +#' The IR Coefficients are estimated using linear least squares. Future +#' Versions will provide support for multivariate data and regularized +#' regression +#' +#' @references +#' Arun K. Tangirala (2015), \emph{Principles of System Identification: +#' Theory and Practice}, CRC Press, Boca Raton. Sections 17.4.11 and 20.2 +#' #' @seealso \code{\link{step}} #' #' @examples @@ -51,7 +60,8 @@ impulseest <- function(data,M=30,K=0,regul=F,lambda=1){ #' Impulse Response Plots #' -#' Plots the estimated IR Coefficients +#' Plots the estimated IR coefficients along with the significance limits +#' at each lag. #' #' @param model an object of class \code{impulseest} #' @param sig Significance Limits (Default: \code{0.975}) @@ -78,6 +88,14 @@ plot.impulseest <- function(model,sig=0.975){ #' @param model an object of class \code{impulseest} #' #' @seealso \code{\link{impulseest}} +#' +#' @examples +#' uk <- rnorm(1000,1) +#' yk <- filter (uk,c(0.9,-0.4),method="recursive") + rnorm(1000,1) +#' data <- idframe(output=data.frame(yk),input=data.frame(uk)) +#' fit <- impulseest(data) +#' step(fit) +#' #' @export step <- function(model){ title <- paste("Step Response \n From",model$x,"to",model$y) diff --git a/man/impulseest.Rd b/man/impulseest.Rd index dd8deb7..30ddf3d 100644 --- a/man/impulseest.Rd +++ b/man/impulseest.Rd @@ -2,7 +2,7 @@ % Please edit documentation in R/nonparam.R \name{impulseest} \alias{impulseest} -\title{Estimate Impulse Response Models} +\title{Estimate Impulse Response Coefficients} \usage{ impulseest(data, M = 30, K = 0, regul = F, lambda = 1) } @@ -21,8 +21,13 @@ used. (Default:\code{FALSE})} \code{regul=TRUE}. (Default:\code{1})} } \description{ -\code{impulseest} is used to estimate impulse response models in the -given data +\code{impulseest} is used to estimate impulse response coefficients from +the data +} +\details{ +The IR Coefficients are estimated using linear least squares. Future +Versions will provide support for multivariate data and regularized +regression } \examples{ uk <- rnorm(1000,1) @@ -31,6 +36,10 @@ data <- idframe(output=data.frame(yk),input=data.frame(uk)) fit <- impulseest(data) plot(fit) } +\references{ +Arun K. Tangirala (2015), \emph{Principles of System Identification: +Theory and Practice}, CRC Press, Boca Raton. Sections 17.4.11 and 20.2 +} \seealso{ \code{\link{step}} } diff --git a/man/plot.impulseest.Rd b/man/plot.impulseest.Rd index b761162..bb273f5 100644 --- a/man/plot.impulseest.Rd +++ b/man/plot.impulseest.Rd @@ -12,7 +12,8 @@ \item{sig}{Significance Limits (Default: \code{0.975})} } \description{ -Plots the estimated IR Coefficients +Plots the estimated IR coefficients along with the significance limits +at each lag. } \seealso{ \code{\link{impulseest}},\code{\link{step}} diff --git a/man/step.Rd b/man/step.Rd index b67b585..b6aa624 100644 --- a/man/step.Rd +++ b/man/step.Rd @@ -12,6 +12,13 @@ step(model) \description{ Plots the step response of a system, given the IR model } +\examples{ +uk <- rnorm(1000,1) +yk <- filter (uk,c(0.9,-0.4),method="recursive") + rnorm(1000,1) +data <- idframe(output=data.frame(yk),input=data.frame(uk)) +fit <- impulseest(data) +step(fit) +} \seealso{ \code{\link{impulseest}} } |