Displaying 3 results from an estimated 3 matches for "ssfit".
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lsfit
2017 Jul 30
4
Kalman filter for a time series
...provider="yahoo",
compression="d", quiet=T)
prices.ts = ts(prices)
return( prices.ts )
}
kalmanFilter = function( x )
{
t = x
if (class(t) != "ts") {
t = ts(t)
}
ssModel = structSSM( y = t, distribution="Gaussian")
ssFit = fitSSM(inits=c(0.5*log(var(t)), 0.5*log(var(t))), model = ssModel )
kfs = KFS( ssFit$model, smoothing="state", nsim=length(t))
vals = kfs$a
lastVal = vals[ length(vals)]
return(lastVal)
}
Start = "2011-01-01"
End = "2012-12-31"
SandP = "^GSPC"
w...
2017 Jul 30
0
Kalman filter for a time series
...ession="d", quiet=T)
>
> prices.ts = ts(prices)
> return( prices.ts )
> }
>
> kalmanFilter = function( x )
> {
> t = x
> if (class(t) != "ts") {
> t = ts(t)
> }
> ssModel = structSSM( y = t, distribution="Gaussian")
> ssFit = fitSSM(inits=c(0.5*log(var(t)), 0.5*log(var(t))), model = ssModel )
> kfs = KFS( ssFit$model, smoothing="state", nsim=length(t))
> vals = kfs$a
> lastVal = vals[ length(vals)]
> return(lastVal)
> }
>
> Start = "2011-01-01"
> End = "2012-12-3...
2017 Jul 30
0
Kalman filter for a time series
...", quiet=T)
>
> prices.ts = ts(prices)
> return( prices.ts )
> }
>
> kalmanFilter = function( x )
> {
> t = x
> if (class(t) != "ts") {
> t = ts(t)
> }
> ssModel = structSSM( y = t, distribution="Gaussian")
> ssFit = fitSSM(inits=c(0.5*log(var(t)), 0.5*log(var(t))), model = ssModel )
> kfs = KFS( ssFit$model, smoothing="state", nsim=length(t))
> vals = kfs$a
> lastVal = vals[ length(vals)]
> return(lastVal)
> }
>
> Start = "2011-01-01"
> End = "20...