ia: Estimate MA coefficients using the innovations algorithm

Description Usage Arguments Details Value See Also Examples

View source: R/itsmr.R

Description

Estimate MA coefficients using the innovations algorithm

Usage

1
ia(x, q, m = 17)

Arguments

x

Time series data (typically residuals from Resid)

q

MA order

m

Recursion level

Details

Normally m should be set to the default value. The innovations algorithm is used to estimate white noise variance.

Value

Returns an ARMA model consisting of a list with the following components.

phi

0

theta

Vector of MA coefficients (index number equals coefficient subscript)

sigma2

White noise variance

aicc

Akaike information criterion corrected

se.phi

0

se.theta

Standard errors for the MA coefficients

See Also

arma burg hannan yw

Examples

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3
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M = c("diff",1)
e = Resid(dowj,M)
a = ia(e,1)
print(a)

Example output

$phi
[1] 0

$theta
[1] 0.4269274

$sigma2
[1] 0.1571672

$aicc
[1] 80.39564

$se.phi
[1] 0

$se.theta
[1] 0.1139606

itsmr documentation built on Sept. 11, 2018, 1:05 a.m.