statsmodels.tsa.filters.filtertools.miso_lfilter(ar, ma, x, useic=False)[source]

use nd convolution to merge inputs, then use lfilter to produce output

arguments for column variables return currently 1d


ar : array_like, 1d, float

autoregressive lag polynomial including lag zero, ar(L)y_t

ma : array_like, same ndim as x, currently 2d

moving average lag polynomial ma(L)x_t

x : array_like, 2d

input data series, time in rows, variables in columns


y : array, 1d

filtered output series

inp : array, 1d

combined input series


currently for 2d inputs only, no choice of axis Use of signal.lfilter requires that ar lag polynomial contains floating point numbers does not cut off invalid starting and final values

miso_lfilter find array y such that:

ar(L)y_t = ma(L)x_t

with shapes y (nobs,), x (nobs,nvars), ar (narlags,), ma (narlags,nvars)