diff options
| -rw-r--r-- | R/poly.R | 18 | ||||
| -rw-r--r-- | man/idpoly.Rd | 16 |
2 files changed, 23 insertions, 11 deletions
@@ -2,13 +2,15 @@ #' #' Creates a polynomial model with identifiable coefficients #' -#' @param A Autoregressive coefficients -#' @param B,F1 Coefficients of the numerator and denominator respectively +#' @param A autoregressive coefficients +#' @param B,F1 coefficients of the numerator and denominator respectively #' of the deterministic model between the input and output -#' @param C,D Coefficients of the numerator and denominator respectively +#' @param C,D coefficients of the numerator and denominator respectively #' of the stochastic model #' @param ioDelay the delay in the input-output channel #' @param Ts sampling interval +#' @param noiseVar variance of the white noise source (Default=\code{1}) +#' @param unit time unit (Default=\code{"seconds"}) #' #' @details #' Discrete-time polynomials are of the form @@ -19,7 +21,8 @@ #' #' @examples #' # define output-error model -#' mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1) +#' mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1, +#' noiseVar = 0.1) #' #' # define box-jenkins model #' B <- c(0.6,-0.2) @@ -29,8 +32,11 @@ #' mod_bj <- idpoly(1,B,C,D,F1,ioDelay=1) #' #' @export -idpoly <- function(A=1,B=1,C=1,D=1,F1=1,ioDelay=0,Ts=1){ - out <- list(A= A,B=B,C=C,D=D,F1=F1,ioDelay = ioDelay,Ts=Ts) +idpoly <- function(A=1,B=1,C=1,D=1,F1=1,ioDelay=0,Ts=1, + noiseVar=1,unit = c("seconds","minutes", + "hours","days")[1]){ + out <- list(A= A,B=B,C=C,D=D,F1=F1,ioDelay = ioDelay,Ts=Ts, + noiseVar=noiseVar,unit=unit) out$type <- typecheck(out) class(out) <- "idpoly" return(out) diff --git a/man/idpoly.Rd b/man/idpoly.Rd index 3f82594..7c33be9 100644 --- a/man/idpoly.Rd +++ b/man/idpoly.Rd @@ -4,20 +4,25 @@ \alias{idpoly} \title{Polynomial model with identifiable parameters} \usage{ -idpoly(A = 1, B = 1, C = 1, D = 1, F1 = 1, ioDelay = 0, Ts = 1) +idpoly(A = 1, B = 1, C = 1, D = 1, F1 = 1, ioDelay = 0, Ts = 1, + noiseVar = 1, unit = c("seconds", "minutes", "hours", "days")[1]) } \arguments{ -\item{A}{Autoregressive coefficients} +\item{A}{autoregressive coefficients} -\item{B, F1}{Coefficients of the numerator and denominator respectively +\item{B, F1}{coefficients of the numerator and denominator respectively of the deterministic model between the input and output} -\item{C, D}{Coefficients of the numerator and denominator respectively +\item{C, D}{coefficients of the numerator and denominator respectively of the stochastic model} \item{ioDelay}{the delay in the input-output channel} \item{Ts}{sampling interval} + +\item{noiseVar}{variance of the white noise source (Default=\code{1})} + +\item{unit}{time unit (Default=\code{"seconds"})} } \description{ Creates a polynomial model with identifiable coefficients @@ -31,7 +36,8 @@ Discrete-time polynomials are of the form } \examples{ # define output-error model -mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1) +mod_oe <- idpoly(B=c(0.6,-0.2),F1=c(1,-0.5),ioDelay = 2,Ts=0.1, +noiseVar = 0.1) # define box-jenkins model B <- c(0.6,-0.2) |