PyLPA
This is a Python package that can be used to run Gaussian mixture models with different constraints on means, variances and covariances. It can thus be used to run latent profile analysis, including multiple group analysis.
Copyright (C) 2023 Johanna Einsiedler
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
Release files for py-latent-profiles 0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| py-latent-profiles-0.4.tar.gz | 15.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| py_latent_profiles-0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.0 kB
Release files / py-latent-profiles-0.4.tar.gz
| Download URL | py-latent-profiles-0.4.tar.gz |
|---|---|
| Size | 15.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / py_latent_profiles-0.4-py3-none-any.whl
| Download URL | py_latent_profiles-0.4-py3-none-any.whl |
|---|---|
| Size | 15.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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twine/4.0.2 CPython/3.11.3
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