Skip to content

Commit

Permalink
CLN: Final clean and rebase
Browse files Browse the repository at this point in the history 
Final pass cleaning and rebasing
Fixed small typos and flake8 issues
  • Loading branch information
@bashtage
bashtage committed May 14, 2017
1 parent 0493843 commit 174fdd9
Showing 1 changed file with 33 additions and 29 deletions.
62 changes: 33 additions & 29 deletions statsmodels/tsa/arima_process.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -7,21 +7,24 @@
* theoretical autocorrelation function of general ARMA
Done, relatively easy to guess solution, time consuming to get
theoretical test cases,
example file contains explicit formulas for acovf of MA(1), MA(2) and ARMA(1,1)
theoretical test cases, example file contains explicit formulas for
acovf of MA(1), MA(2) and ARMA(1,1)
Properties:
Judge, ... (1985): The Theory and Practise of Econometrics
Author: josefpktd
License: BSD
"""
from __future__ import print_function
from statsmodels.compat.python import range

import numpy as np
from scipy import signal, optimize, linalg

__all__ = ['arma_acf', 'arma_acovf', 'arma_generate_sample',
'arma_impulse_response', 'arma2ar', 'arma2ma', 'deconvolve',
'lpol2index', 'index2lpol']


def arma_generate_sample(ar, ma, nsample, sigma=1, distrvs=np.random.randn,
burnin=0):
Expand All @@ -44,7 +47,7 @@ def arma_generate_sample(ar, ma, nsample, sigma=1, distrvs=np.random.randn,
default: np.random.randn
TODO: change to size argument
burnin : integer
Burnin observations at the geneated and dropped from the beginning of
Burn in observations at the generated and dropped from the beginning of
the sample
Returns
Expand All @@ -57,7 +60,7 @@ def arma_generate_sample(ar, ma, nsample, sigma=1, distrvs=np.random.randn,
As mentioned above, both the AR and MA components should include the
coefficient on the zero-lag. This is typically 1. Further, due to the
conventions used in signal processing used in signal.lfilter vs.
conventions in statistics for ARMA processes, the AR paramters should
conventions in statistics for ARMA processes, the AR parameters should
have the opposite sign of what you might expect. See the examples below.
Examples
Expand Down Expand Up @@ -105,7 +108,7 @@ def arma_acovf(ar, ma, nobs=10):
Notes
-----
Tries to do some crude numerical speed improvements for cases
with high persistance. However, this algorithm is slow if the process is
with high persistence. However, this algorithm is slow if the process is
highly persistent and only a few autocovariances are desired.
"""
# increase length of impulse response for AR closer to 1
Expand All @@ -117,7 +120,7 @@ def arma_acovf(ar, ma, nobs=10):
else:
nobs_ir = max(100, 2 * nobs) # no idea right now
ir = arma_impulse_response(ar, ma, leads=nobs_ir)
# better save than sorry (?), I have no idea about the required precision
# better safe than sorry (?), I have no idea about the required precision
# only checked for AR(1)
while ir[-1] > 5 * 1e-5:
nobs_ir *= 10
Expand Down Expand Up @@ -159,7 +162,8 @@ def arma_acf(ar, ma, lags=10, **kwargs):
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags', DeprecationWarning)
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)

acovf = arma_acovf(ar, ma, lags)
return acovf / acovf[0]
Expand Down Expand Up @@ -192,7 +196,8 @@ def arma_pacf(ar, ma, lags=10, **kwargs):
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags', DeprecationWarning)
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
# TODO: Should use rank 1 inverse update
apacf = np.zeros(lags)
acov = arma_acf(ar, ma, lags=lags + 1)
Expand All @@ -215,7 +220,7 @@ def arma_periodogram(ar, ma, worN=None, whole=0):
ma : array_like
moving average lag-polynomial with leading 1
worN : {None, int}, optional
option for scipy.signal.freqz (read "w or N")
option for scipy.signal.freqz (read "w or N")
If None, then compute at 512 frequencies around the unit circle.
If a single integer, the compute at that many frequencies.
Otherwise, compute the response at frequencies given in worN
Expand All @@ -242,7 +247,9 @@ def arma_periodogram(ar, ma, worN=None, whole=0):
sd = np.abs(h) ** 2 / np.sqrt(2 * np.pi)
if np.any(np.isnan(h)):
# this happens with unit root or seasonal unit root'
print('Warning: nan in frequency response h, maybe a unit root')
import warnings
warnings.warn('Warning: nan in frequency response h, maybe a unit '
'root', RuntimeWarning)
return w, sd


Expand Down Expand Up @@ -273,7 +280,7 @@ def arma_impulse_response(ar, ma, leads=100, **kwargs):
ma_representation = arma_impulse_response(ar, ma, leads=100)
ar_representation = arma_impulse_response(ma, ar, leads=100)
fully tested against matlab
Fully tested against matlab
Examples
--------
Expand Down Expand Up @@ -303,7 +310,8 @@ def arma_impulse_response(ar, ma, leads=100, **kwargs):
if 'nobs' in kwargs:
leads = kwargs['nobs']
import warnings
warnings.warn(DeprecationWarning, 'nobs is deprecated in favor of leads')
warnings.warn('nobs is deprecated in favor of leads',
DeprecationWarning)
impulse = np.zeros(leads)
impulse[0] = 1.
return signal.lfilter(ma, ar, impulse)
Expand Down Expand Up @@ -338,7 +346,8 @@ def arma2ma(ar, ma, lags=100, **kwargs):
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags', DeprecationWarning)
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)

return arma_impulse_response(ar, ma, leads=lags)

Expand Down Expand Up @@ -372,7 +381,8 @@ def arma2ar(ar, ma, lags=100, **kwargs):
if 'nobs' in kwargs:
lags = kwargs['nobs']
import warnings
warnings.warn('nobs is deprecated in favor of lags', DeprecationWarning)
warnings.warn('nobs is deprecated in favor of lags',
DeprecationWarning)
return arma_impulse_response(ma, ar, leads=lags)


Expand Down Expand Up @@ -415,7 +425,7 @@ def ar2arma(ar_des, p, q, n=20, mse='ar', start=None):
"""

# TODO: convert MA lag polynomial, ma_app, to be invertible, by mirroring
# TODO: roots outside the unit intervall to ones that are inside. How do we do
# TODO: roots outside the unit interval to ones that are inside. How to do
# TODO: this?

# p,q = pq
Expand All @@ -437,7 +447,7 @@ def msear_err(arma, ar_des):

def lpol2index(ar):
"""
Remove zeros from lagpolynomial
Remove zeros from lag polynomial
Parameters
----------
Expand All @@ -449,7 +459,7 @@ def lpol2index(ar):
coeffs : array
non-zero coefficients of lag polynomial
index : array
index (lags) of lagpolynomial with non-zero elements
index (lags) of lag polynomial with non-zero elements
"""
ar = np.asarray(ar)
index = np.nonzero(ar)[0]
Expand All @@ -466,7 +476,7 @@ def index2lpol(coeffs, index):
coeffs : array
non-zero coefficients of lag polynomial
index : array
index (lags) of lagpolynomial with non-zero elements
index (lags) of lag polynomial with non-zero elements
Returns
-------
Expand Down Expand Up @@ -623,7 +633,7 @@ class ArmaProcess(object):
Both the AR and MA components must include the coefficient on the
zero-lag. In almost all cases these values should be 1. Further, due to
using the lag-polynomial representation, the AR parameters should
have the opposite sign of what one would write in the ARMA representaion.
have the opposite sign of what one would write in the ARMA representation.
See the examples below.
The ARMA(p,q) process is described by
Expand Down Expand Up @@ -742,10 +752,9 @@ def __mul__(self, oth):
return self.__class__(ar, ma, nobs=self.nobs)

def __repr__(self):
return 'ArmaProcess({0}, {1}, nobs={2}) at {3}'.format(self.ar.tolist(),
self.ma.tolist(),
self.nobs,
hex(id(self)))
msg = 'ArmaProcess({0}, {1}, nobs={2}) at {3}'
return msg.format(self.ar.tolist(), self.ma.tolist(),
self.nobs, hex(id(self)))

def __str__(self):
return 'ArmaProcess\nAR: {0}\nMA: {1}'.format(self.ar.tolist(),
Expand Down Expand Up @@ -922,8 +931,3 @@ def generate_sample(self, nsample=100, scale=1., distrvs=None, axis=0,
fslice = tuple([slice(None)] * np.ndim(newsize))
eta = scale * distrvs(size=newsize)
return signal.lfilter(self.ma, self.ar, eta, axis=axis)[fslice]


__all__ = ['arma_acf', 'arma_acovf', 'arma_generate_sample',
'arma_impulse_response', 'arma2ar', 'arma2ma', 'deconvolve',
'lpol2index', 'index2lpol']

0 comments on commit 174fdd9

Please sign in to comment.