Description Usage Arguments Details Value Note Author(s) References See Also Examples
Fits a multiple linear regression with FGN errors
1 | FitRegressionFGN(X, y)
|
X |
design matrix, must include column of 1's if constant term is present |
y |
the response variable, a time series |
An iterative algorithm is used to compute the exact MLE.
a list with 3 elements:
Loglikelihood |
value of the maximized loglikelihood |
H |
MLE for H |
alpha |
MLE for regression coefficients corresponding to colums of X |
It is assumed that X is not collinear.
A.I. McLeod
McLeod, A.I., Yu, Hao, Krougly, Zinovi L. (2007). Algorithms for Linear Time Series Analysis, Journal of Statistical Software.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | #simulate FGN with mean zero and H=0.2 and fit exact mle for H and mean
H<-0.2
z<-SimulateFGN(512, H)
mean(z)
X<-matrix(rep(1,length(z)), ncol=1)
ans<-FitRegressionFGN(X,z)
ans
#fit a step intervention model to the Nile annual riverflow data
data(NileFlowCMS)
n<-length(NileFlowCMS)
X<-matrix(c(rep(1,n),rep(0,32),rep(1,n-32)),ncol=2)
ans<-FitRegressionFGN(X,NileFlowCMS)
ans
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