README.md
In benkeser/predtmle: Small sample estimators of cross-validated prediction metrics
R/predtmle
Small sample estimators of cross-validated prediction metrics
Authors: David Benkeser
Description
predtmle is an R package for computing estimates of cross-validated
prediction metrics. These estimates are tailored for superior
performance in small samples. Several estimators are available including
ones based cross-validated targeted minimum loss-based estimation,
estimating equations, and one-step estimation.
Installation
Issues
If you encounter any bugs or have any specific feature requests, please
file an issue.
Example
Contributions
Interested contributors can consult our contribution
guidelines
prior to submitting a pull request.
Citation
— –>
License
© 2018 David C. Benkeser
The contents of this repository are distributed under the MIT license.
See below for details:
The MIT License (MIT)
Copyright (c) 2018 David C. Benkeser
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
benkeser/predtmle documentation built on May 20, 2019, 5:41 p.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
R/predtmle
Small sample estimators of cross-validated prediction metrics
Authors: David Benkeser
Description
predtmle is an R package for computing estimates of cross-validated
prediction metrics. These estimates are tailored for superior
performance in small samples. Several estimators are available including
ones based cross-validated targeted minimum loss-based estimation,
estimating equations, and one-step estimation.
Installation
Issues
If you encounter any bugs or have any specific feature requests, please file an issue.
Example
Contributions
Interested contributors can consult our contribution
guidelines
prior to submitting a pull request.
Citation
— –>
License
© 2018 David C. Benkeser
The contents of this repository are distributed under the MIT license. See below for details:
The MIT License (MIT)
Copyright (c) 2018 David C. Benkeser
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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