Python's forecast::auto.arima equivalent

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

Supported versions

pyramid

Pyramid is a no-nonsense statistical Python library with a solitary objective: bring R's auto.arima functionality to Python. Pyramid operates by wrapping statsmodels.tsa.ARIMA and statsmodels.tsa.statespace.SARIMAX into one estimator class and creating a more user-friendly estimator interface for programmers familiar with scikit-learn.

Installation

Pyramid is on pypi under the package name pyramid-arima and can be downloaded via pip:

$ pip install pyramid-arima

To ensure the package was built correctly, import the following module in python:

from pyramid.arima import auto_arima

Documentation

All of your questions and more (including examples and guides) can be answered by the Pyramid documentation. If not, always feel free to file an issue.

Project details

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

0.9.0

Nov 2, 2018

0.8.1

Aug 30, 2018

0.7.1

Aug 14, 2018

0.6.5

Mar 27, 2018

0.6.2

Nov 13, 2017

0.5.1

Aug 28, 2017

0.5

Aug 26, 2017

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

pyramid_arima-0.9.0-cp36-cp36m-win_amd64.whl (198.6 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.6m Windows x86-64

pyramid_arima-0.9.0-cp36-cp36m-win32.whl (174.0 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.6m Windows x86

pyramid_arima-0.9.0-cp36-cp36m-manylinux1_x86_64.whl (598.0 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.6m

pyramid_arima-0.9.0-cp35-cp35m-win_amd64.whl (197.3 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.5m Windows x86-64

pyramid_arima-0.9.0-cp35-cp35m-win32.whl (173.4 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.5m Windows x86

pyramid_arima-0.9.0-cp35-cp35m-manylinux1_x86_64.whl (599.0 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.5m

pyramid_arima-0.9.0-cp35-cp35m-macosx_10_6_x86_64.whl (200.5 kB view hashes)

Uploaded Nov 2, 2018 CPython 3.5m macOS 10.6+ x86-64

pyramid_arima-0.9.0-cp27-cp27mu-manylinux1_x86_64.whl (575.7 kB view hashes)

Uploaded Nov 2, 2018 CPython 2.7mu

pyramid_arima-0.9.0-cp27-cp27m-win_amd64.whl (205.3 kB view hashes)

Uploaded Nov 2, 2018 CPython 2.7m Windows x86-64

pyramid_arima-0.9.0-cp27-cp27m-win32.whl (180.5 kB view hashes)

Uploaded Nov 2, 2018 CPython 2.7m Windows x86

pyramid_arima-0.9.0-cp27-cp27m-manylinux1_x86_64.whl (569.2 kB view hashes)

Uploaded Nov 2, 2018 CPython 2.7m

pyramid_arima-0.9.0-cp27-cp27m-macosx_10_6_x86_64.whl (208.8 kB view hashes)

Uploaded Nov 2, 2018 CPython 2.7m macOS 10.6+ x86-64

Hashes for pyramid_arima-0.9.0-cp36-cp36m-win_amd64.whl

Hashes for pyramid_arima-0.9.0-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`fc0e7c769b8c012d2bbee0c19bad28a93f9e76f04babcb181163dd07d23ad942`
MD5	`722bbb3c7935cdd81a70b762ce94a631`
BLAKE2b-256	`ed7e0032cf67571d67e01e0541893014ebeb412dfa973d159c90a8ab73a92ce8`

Hashes for pyramid_arima-0.9.0-cp36-cp36m-win32.whl

Hashes for pyramid_arima-0.9.0-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`12c94023f536aae5a2d1ef7e4ce25bbb49bd85e4394624cba5be7740317c5e2d`
MD5	`122aee1e0efd4cb916209d978705bbbd`
BLAKE2b-256	`45b3c739d707a53c6a58d646697d1e03dc86d061ba60fc04c3c119d6f110a205`

Hashes for pyramid_arima-0.9.0-cp36-cp36m-manylinux1_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`7253569af6c3df8a47803a7fbc8f04675253cd99314b0c13317e4215d51ca0b4`
MD5	`aa39c260546ece16ff2887e29f353c96`
BLAKE2b-256	`5c8457422f2a6ade3161c586545e38b518ba1b7ab30ee4a4acc29110c0aba2bc`

Hashes for pyramid_arima-0.9.0-cp35-cp35m-win_amd64.whl

Hashes for pyramid_arima-0.9.0-cp35-cp35m-win_amd64.whl
Algorithm	Hash digest
SHA256	`80bb4899f33125c06ac55f061d0c95641bb172161e54a52a2c18915dd0c60e2e`
MD5	`d7b72456952e83dca801d7667494dc44`
BLAKE2b-256	`d76edff43fecb7735cbd58950b4f4cb1ba5658e09838ff232c727c82fd361b0f`

Hashes for pyramid_arima-0.9.0-cp35-cp35m-win32.whl

Hashes for pyramid_arima-0.9.0-cp35-cp35m-win32.whl
Algorithm	Hash digest
SHA256	`26214231e973a88de2badfc0076cd30a67b2fdb0c4031f63104e4ddacb992f7a`
MD5	`d7fc1fc4ccbde7be14778c41f64cef07`
BLAKE2b-256	`d33564ca4ac5f8218667ec348d7c9b0e33cae08f4462c15bdf8e6ac9e70b8849`

Hashes for pyramid_arima-0.9.0-cp35-cp35m-manylinux1_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`38adb548a30fbfa7700415c1d8be755441e0e3b23532744d5acf00d6c78efd82`
MD5	`31369a9350e3ed04a9602ff40e14f90b`
BLAKE2b-256	`e7cac7c96a64593a3a8a4e752f1da906044f919ba2be68718b27b059e55d7364`

Hashes for pyramid_arima-0.9.0-cp35-cp35m-macosx_10_6_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp35-cp35m-macosx_10_6_x86_64.whl
Algorithm	Hash digest
SHA256	`e167ce88b436e7a0c1592ce02566c11f43082e0ab8198514f476805208f14bf9`
MD5	`76798b5d8a1bcdcdd2441757d1fce99b`
BLAKE2b-256	`b5f0b9c689e74c13de8de210df0328ceaaf410bcb9334e9bc707892708b48bba`

Hashes for pyramid_arima-0.9.0-cp27-cp27mu-manylinux1_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`e6949ab23dc958547b2ed35e4b793835156201c98d5c3f3ab357e448f17f30a6`
MD5	`2b7dc0917e570a802bb4399ea6f8303b`
BLAKE2b-256	`32e5df736fe210128be58f134807df273908ede31e01b18eee45fe68af268950`

Hashes for pyramid_arima-0.9.0-cp27-cp27m-win_amd64.whl

Hashes for pyramid_arima-0.9.0-cp27-cp27m-win_amd64.whl
Algorithm	Hash digest
SHA256	`606ce8759604b9555a78a5eec05fbd9a18f6a26eacfa056a7dfc71bb0f20e09e`
MD5	`07b0b5273cf92864f565a8928214d1f9`
BLAKE2b-256	`a30f5bbff57118bd3221a6e12a4c2c7870347014f01dc03f418cbb368d183b9d`

Hashes for pyramid_arima-0.9.0-cp27-cp27m-win32.whl

Hashes for pyramid_arima-0.9.0-cp27-cp27m-win32.whl
Algorithm	Hash digest
SHA256	`e6ff3c0c550eece36576401e1457754dcc86725082c1863c8e9212d0e62281a7`
MD5	`59417c27d0c4e085116fdf2efaf7ea89`
BLAKE2b-256	`4ca68a9c3ee267ef5a1d6523c52a40104860054d97a842e466852310e4966ca8`

Hashes for pyramid_arima-0.9.0-cp27-cp27m-manylinux1_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp27-cp27m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`6062bff994da2a7355cfdd873c1d6846ed7d7ffc65b366c0552efe7c81686e89`
MD5	`fcc2f11e1aa035460f712b7ae7b7eced`
BLAKE2b-256	`f4cbc486f716b56e4cfa5b99305ec315774b4d5dca60c4a9b4219be1729c659c`

Hashes for pyramid_arima-0.9.0-cp27-cp27m-macosx_10_6_x86_64.whl

Hashes for pyramid_arima-0.9.0-cp27-cp27m-macosx_10_6_x86_64.whl
Algorithm	Hash digest
SHA256	`c22c9e8dd8c3ff6ddb52081d60fe842d9b25ed7c15f75dfa1e282f176375138d`
MD5	`07cfec1741d23c36a6ddaa227efc0192`
BLAKE2b-256	`e8169b45aa37469b14ab9a5b29c9bbc2a4e29d33a18d21405ccc229fe8ce726e`