Simulate_new_MA function

Simulate a new Moving Average (MA) vector time series and return the time series

Simulate_new_MA(a, T.len, noise.type, DEBUG = FALSE)

Arguments

• a: Array, returned by Generate_filterMA, containing the filter of the MA process
• T.len: Numeric, the length of the time series to generate
• noise.type: the type of noise that is driving the MA process. See Details section.
• DEBUG: Logical, for outputting information on the progress of the function

Returns

A T.len x dim(a)[1] matrix, where each column corresponds to a coordinate of the vector time series

Details

The function simulates a moving average process of dimension dim(a)[1], defined by

noise.type specifies the nature and internal correlation of the noise that is driving the MA process. It can take the values

• white-noise: the noise is Gaussian with covariance matrix identity
• white-noise: the noise is Gaussian with diagonal covariance matrix, whose j-th diagonal entry is $((j - 0.5 )*pi)^(-1)$
• studentk: the coordinates of the noise are independent and have a student t distribution with 'k' degrees of freedom, standardized to have variance 1

Examples

ma.scale1=c(-1.4,2.3,-2)
a1=Generate_filterMA(6, 6, MA.len=3, ma.scale=ma.scale1)
X=Simulate_new_MA(a1, T.len=512, noise.type='wiener')
plot.ts(X)