49 lines
2.2 KiB
Python
49 lines
2.2 KiB
Python
# scipy-yli: Helpful SciPy utilities and recipes
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# Copyright © 2022–2023 Lee Yingtong Li (RunasSudo)
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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#
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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from pytest import approx
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import pandas as pd
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import yli
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def test_afbf_logit_beta_zero():
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"""Compare RegressionModel.bayesfactor_beta_zero for Ott & Longnecker (2016) chapter 12.23 with R BFpack"""
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df = pd.DataFrame({
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'Unhealthy': [False, False, False, False, False, False, False, True, False, False, False, True, False, False, False, False, False, False, True, False, True, False, False, False, False, False, True, False, False, True, False, False],
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'Fibrinogen': [2.52, 2.46, 2.29, 3.15, 2.88, 2.29, 2.99, 2.38, 2.56, 3.22, 2.35, 3.53, 2.65, 2.15, 3.32, 2.23, 2.19, 2.21, 5.06, 2.68, 2.09, 2.54, 2.18, 2.68, 3.41, 3.15, 3.35, 2.60, 2.28, 3.93, 2.60, 3.34],
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'GammaGlobulin': [38, 36, 36, 36, 30, 31, 36, 37, 31, 38, 29, 46, 46, 31, 35, 37, 33, 37, 37, 34, 44, 28, 31, 39, 37, 39, 32, 38, 36, 32, 41, 30]
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})
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result = yli.regress(yli.Logit, df, 'Unhealthy', 'Fibrinogen + GammaGlobulin')
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# model <- glm(Unhealthy ~ Fibrinogen + GammaGlobulin, data=df, family=binomial())
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# bf_fit <- BF(model, hypothesis="Fibrinogen = 0")
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# summary(bf_fit)
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# bf_fit <- BF(model, hypothesis="GammaGlobulin = 0")
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# summary(bf_fit)
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bf = result.bayesfactor_beta_zero('Fibrinogen')
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assert bf.factor == approx(1.229, abs=0.001)
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assert bf.num_desc == 'Fibrinogen ≠ 0'
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assert bf.denom_desc == 'Fibrinogen = 0'
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bf = result.bayesfactor_beta_zero('GammaGlobulin')
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assert bf.factor == approx(2.417, abs=0.001)
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assert bf.num_desc == 'GammaGlobulin = 0'
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assert bf.denom_desc == 'GammaGlobulin ≠ 0'
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