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Merge pull request #632 from bashtage/fix-clustered
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DOC: Change "cluster" to "clustered" in the docs
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bashtage authored Dec 11, 2024
2 parents 3111b39 + ad5b964 commit 1969b5b
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Showing 10 changed files with 9 additions and 40 deletions.
1 change: 1 addition & 0 deletions ci/azure_template_posix.yml
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Expand Up @@ -100,6 +100,7 @@ jobs:
flake8 linearmodels
black --check linearmodels
isort --check linearmodels
ruff check linearmodels
displayName: 'Check style and formatting'
- script: |
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12 changes: 0 additions & 12 deletions linearmodels/compat/formulaic.py

This file was deleted.

5 changes: 0 additions & 5 deletions linearmodels/iv/_utility.py
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Expand Up @@ -13,11 +13,6 @@

import linearmodels.typing.data

from ..compat.formulaic import monkey_patch_materializers

# Monkey patch parsers if needed, remove once formulaic updated
monkey_patch_materializers()

PARSING_ERROR = """
Conversion of formula blocks to DataFrames failed.
The formula blocks used for conversion were:
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2 changes: 1 addition & 1 deletion linearmodels/iv/absorbing.py
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Expand Up @@ -1020,7 +1020,7 @@ def fit(
* "robust", "heteroskedastic" - Heteroskedasticity robust inference
* "kernel" - Heteroskedasticity and autocorrelation robust
inference
* "cluster" - One-way cluster dependent inference.
* "clustered" - One-way cluster dependent inference.
Heteroskedasticity robust
debiased : bool
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2 changes: 1 addition & 1 deletion linearmodels/iv/gmm.py
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Expand Up @@ -380,7 +380,7 @@ class IVGMMCovariance(HomoskedasticCovariance):
* "robust", "heteroskedastic" - Allows for heteroskedasticity by not
autocorrelation
* "kernel" - Allows for heteroskedasticity and autocorrelation
* "cluster" - Allows for one-way cluster dependence
* "clustered" - Allows for one-way cluster dependence
debiased : bool
Flag indicating whether to debias the covariance estimator
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10 changes: 5 additions & 5 deletions linearmodels/iv/model.py
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Expand Up @@ -632,7 +632,7 @@ def fit(
* "robust", "heteroskedastic" - Heteroskedasticity robust inference
* "kernel" - Heteroskedasticity and autocorrelation robust
inference
* "cluster" - One-way cluster dependent inference.
* "clustered" - One-way cluster dependent inference.
Heteroskedasticity robust
debiased : bool
Expand Down Expand Up @@ -976,7 +976,7 @@ class _IVGMMBase(_IVModelBase):
* "robust", "heteroskedastic" - Allows for heteroskedasticity by not
autocorrelation
* "kernel" - Allows for heteroskedasticity and autocorrelation
* "cluster" - Allows for one-way cluster dependence
* "clustered" - Allows for one-way cluster dependence
The estimator is defined as
Expand Down Expand Up @@ -1079,7 +1079,7 @@ class IVGMM(_IVGMMBase):
* "robust", "heteroskedastic" - Allows for heteroskedasticity by not
autocorrelation
* "kernel" - Allows for heteroskedasticity and autocorrelation
* "cluster" - Allows for one-way cluster dependence
* "clustered" - Allows for one-way cluster dependence
The estimator is defined as
Expand Down Expand Up @@ -1245,7 +1245,7 @@ def fit(
* "robust", "heteroskedastic" - Allows for heteroskedasticity but
not autocorrelation
* "kernel" - Allows for heteroskedasticity and autocorrelation
* "cluster" - Allows for one-way cluster dependence
* "clustered" - Allows for one-way cluster dependence
debiased : bool
Flag indicating whether to debiased the covariance estimator using
Expand Down Expand Up @@ -1355,7 +1355,7 @@ class IVGMMCUE(_IVGMMBase):
* "robust", "heteroskedastic" - Allows for heteroskedasticity by not
autocorrelation
* "kernel" - Allows for heteroskedasticity and autocorrelation
* "cluster" - Allows for one-way cluster dependence
* "clustered" - Allows for one-way cluster dependence
In most circumstances, the ``center`` weight option should be ``True`` to
avoid starting value dependence.
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5 changes: 0 additions & 5 deletions linearmodels/panel/model.py
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@@ -1,7 +1,5 @@
from __future__ import annotations

from linearmodels.compat.formulaic import monkey_patch_materializers

from collections.abc import Mapping
from typing import Any, NamedTuple, Union, cast

Expand Down Expand Up @@ -58,9 +56,6 @@
from linearmodels.shared.utility import AttrDict, ensure_unique_column, panel_to_frame
import linearmodels.typing.data

# Monkey patch parsers if needed, remove once formulaic updated
monkey_patch_materializers()

CovarianceEstimator = Union[
ACCovariance,
ClusteredCovariance,
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5 changes: 0 additions & 5 deletions linearmodels/shared/hypotheses.py
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@@ -1,7 +1,5 @@
from __future__ import annotations

from linearmodels.compat.formulaic import monkey_patch_materializers

from collections.abc import Mapping

from formulaic.utils.constraints import LinearConstraints
Expand All @@ -11,9 +9,6 @@

import linearmodels.typing.data

# Monkey patch parsers if needed, remove once formulaic updated
monkey_patch_materializers()


class WaldTestStatistic:
"""
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5 changes: 0 additions & 5 deletions linearmodels/system/model.py
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Expand Up @@ -14,8 +14,6 @@

from __future__ import annotations

from linearmodels.compat.formulaic import monkey_patch_materializers

from collections.abc import Mapping, Sequence
from functools import reduce
import textwrap
Expand Down Expand Up @@ -61,9 +59,6 @@

__all__ = ["SUR", "IV3SLS", "IVSystemGMM", "LinearConstraint"]

# Monkey patch parsers if needed, remove once formulaic updated
monkey_patch_materializers()

UNKNOWN_EQ_TYPE = """
Contents of each equation must be either a dictionary with keys "dependent"
and "exog" or a 2-element tuple of he form (dependent, exog).
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2 changes: 1 addition & 1 deletion requirements.txt
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Expand Up @@ -5,6 +5,6 @@ statsmodels>=0.13.0
mypy_extensions>=0.4
Cython>=3.0.10
pyhdfe>=0.1
formulaic>=1.0.0
formulaic>=1.0.2
# versioning
setuptools_scm[toml]>=8.0.0,<9.0.0

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