statsmodels.tsa.filters.filtertools.miso_lfilter
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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
Parameters: 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
Returns: y : array, 1d
filtered output series
inp : array, 1d
combined input series
Notes
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)
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