Expected large-sample information matrix for ARMA

Description

The expected large-sample information matrix per observation for ARMA(p,q) models is computed.

Usage

InformationMatrixARMA(phi = numeric(0), theta = numeric(0))

Arguments

Details

The information matrix is derived by Box and Jenkins (1970).

Value

a matrix of order (p+q)

Author(s)

A.I. McLeod

References

Box and Jenkins (1970). Time Series Analysis: Forecasting and Control.

See Also

FitARMA

Examples

#The covariance matrix estimates of the parameters phi and theta in an ARMA(1,1)
#with phi=0.9 and theta=0.5 and n=200 is
v<-solve(InformationMatrixARMA(0.9,0.5))/200
v
#and the standard errors are
sqrt(diag(v))
  

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> library(FitARMA)
Loading required package: FitAR
Loading required package: lattice
Loading required package: leaps
Loading required package: ltsa
Loading required package: bestglm
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/FitARMA/InformationMatrixARMA.Rd_%03d_medium.png", width=480, height=480)
> ### Name: InformationMatrixARMA
> ### Title: Expected large-sample information matrix for ARMA
> ### Aliases: InformationMatrixARMA
> ### Keywords: ts
> 
> ### ** Examples
> 
> #The covariance matrix estimates of the parameters phi and theta in an ARMA(1,1)
> #with phi=0.9 and theta=0.5 and n=200 is
> v<-solve(InformationMatrixARMA(0.9,0.5))/200
> v
              phi(1)    theta(1)
phi(1)   0.001796094 0.002449219
theta(1) 0.002449219 0.007089844
> #and the standard errors are
> sqrt(diag(v))
    phi(1)   theta(1) 
0.04238035 0.08420121 
>   
> 
> 
> 
> 
> dev.off()
null device 
          1 
>