tmle3mopttx VS lmtp

Compare tmle3mopttx vs lmtp and see what are their differences.

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tmle3mopttx lmtp
1 1
10 53
- -
0.0 5.2
over 1 year ago 25 days ago
R R
GNU General Public License v3.0 only GNU Affero General Public License v3.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

tmle3mopttx

Posts with mentions or reviews of tmle3mopttx. We have used some of these posts to build our list of alternatives and similar projects.

lmtp

Posts with mentions or reviews of lmtp. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-12.
  • [Q] Should G-methods, IPTW always be used over traditional regression?
    4 projects | /r/statistics | 12 Sep 2021
    The tlverse/sl3 super learner library is much better integrated and a lot more powerful (a bit more complicated in the beginning but once you understand it, its great). LMTP has a separate branch that uses sl3: https://github.com/nt-williams/lmtp/tree/sl3-devel. To specify formulas is sl3, you just do Lrnr_glmnet$new(formula = ~ 1 + W + A + A*W), but make sure to download the "dev" version: devtools::install_github("tlverse/sl3", ref = "devel").

What are some alternatives?

When comparing tmle3mopttx and lmtp you can also consider the following projects:

ParBayesianOptimization - Parallelizable Bayesian Optimization in R

causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

vip - Variable Importance Plots (VIPs)

sjPlot - sjPlot - Data Visualization for Statistics in Social Science

textfeatures - 👷‍♂️ A simple package for extracting useful features from character objects 👷‍♀️

MicrobiomeStat - Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat

hermiter - Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)

hal9001 - 🤠 📿 The Highly Adaptive Lasso