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freqdom (version 2.0.5)

timedom: Defines a linear filter

Description

Creates an object of class timedom. This object corresponds to a multivariate linear filter.

Usage

timedom(A, lags)

Value

Returns an object of class timedom. An object of class timedom is a list containing the following components:

  • operators \(\quad\) returns the array A as given in the argument.

  • lags \(\quad\) returns the vector lags as given in the argument.

Arguments

A

a vector, matrix or array. If array, the elements \(A[,,k], 1\leq k\leq K\), are real valued \((d_1\times d_2)\) matrices (all of same dimension). If A is a matrix, the \(k\)-th row is treated as \(A[,,k]\). Same for the \(k\)-th element of a vector. These matrices, vectors or scalars define a linear filter.

lags

a vector of increasing integers. It corresponds to the time lags of the filter.

Details

This class is used to describe a linear filter, i.e. a sequence of matrices, each of which correspond to a certain lag. Filters can, for example, be used to transform a sequence \((X_t)\) into a new sequence \((Y_t)\) by defining $$ Y_t=\sum_k A_kX_{t-k}. $$ See filter.process(). Formally we consider a collection \([A_1,\ldots,A_K]\) of complex-valued matrices \(A_k\), all of which have the same dimension \(d_1\times d_2\). Moreover, we consider lags \(\ell_1<\ell_2<\cdots<\ell_K\). The object this function creates corresponds to the mapping \(f: \mathrm{lags}\to \mathbf{R}^{d_1\times d_2}\), where \(\ell_k\mapsto A_k\).

See Also

freqdom, is.timedom

Examples

Run this code
# In this example we apply the difference operator: Delta X_t= X_t-X_{t-1} to a time series
X = rar(20)
OP = array(0,c(2,2,2))
OP[,,1] = diag(2)
OP[,,2] = -diag(2)
A = timedom(OP, lags = c(0,1))
filter.process(X, A)

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