1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
|
predict.idpoly <- function(x,data,nahead=1){
y <- outputData(data); u<- inputData(data)
G <- signal::Arma(b=c(rep(0,x$ioDelay),x$B),
a= as.numeric(polynom::polynomial(x$A)*
polynom::polynomial(x$F1)))
det_sys <- as.numeric(signal::filter(G,u))
if(x$type=="oe" || nahead==Inf){
ypred <- det_sys
} else{
Hden <- as.numeric(polynom::polynomial(x$A)*polynom::polynomial(x$D))
Hinv <- signal::Arma(b=Hden,a=x$C)
filtered <- as.numeric(signal::filter(Hinv,as.numeric(y)-det_sys))
if(nahead!=1){
H <- as.numeric(polynom::polynomial(x$C)*polyinv(Hden,nahead))
Hl <- signal::Ma(H[1:nahead])
filtered <- as.numeric(signal::filter(Hl,filtered))
}
ypred <- as.numeric(y) - filtered
}
ts(ypred,start=start(data),deltat=deltat(data))
}
polyinv <- function(x,k){
gamma <- 1/Re(polyroot(x))
inverse <- function(y,k){
sapply(1:k-1,function(i) y^i)
}
z <- lapply(lapply(gamma,inverse,k=2),polynom::polynomial)
temp = z[[1]]
if(length(z)>1){
for(i in 2:length(z)){
temp = temp*z[[i]]
}
}
temp
}
#' @export
predict.estpoly <- function(x,newdata=NULL,nahead=1){
if(is.null(newdata)&& nahead==1){
return(fitted(x))
} else{
model <- x$sys
if(is.null(newdata)){
y <- fitted(x)+resid(x)
u <- x$input
z <- idframe(y,u,Ts = deltat(y),start=start(y))
} else{
z <- newdata
}
predict(model,z,nahead)
}
}
#' @import ggplot2 reshape
#' @export
compare <- function(){
}
|
