Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
-
Updated
Apr 7, 2022 - R
Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning
first project in C++, tried to build model of Protparam Expassy working source code to analyze the properties of proteins like molecular weight, theoretical pI, extinction coefficient, percentage of charged amino acid and composition.
Add a description, image, and links to the working-model topic page so that developers can more easily learn about it.
To associate your repository with the working-model topic, visit your repo's landing page and select "manage topics."