Byron

title

introduce `ltry`

1

currently oblique forests just try to make one linear combination of predictors, and they will try again (with different predictors) if that split isn't good enough. There should be more...

this is an idea to make oblique RFs more explainable for a single prediction: 1. pull out the regression coefficients from the node directly above the given obervation's predicted leaf...

utility functions for logistic regression and ols

1

default methods to find linear combos of predictors in classification and regression trees

aorsf time prediction

3

See https://github.com/ropensci/aorsf/issues/49 - Updates default oobag prediction type to match `aorsf` v0.1.3 - Adds code for survival time prediction with `aorsf`, and a test.

aorsf classification and regression engines

1

Adds support for `aorsf` (#73). I am uploading `aorsf` version 0.1.4 to CRAN and I don't expect any problems, but I totally understand if you'd prefer we hold off on...

Allow `Y.hat` input for `causal_survival_forest()`?

9

Hello, Thank you for developing `grf`. It's great! Would it be feasible to allow `Y.hat` to be an input for causal survival forests? I see from code in `causal_survival_forest` that...

If mtry is 1, the regression coefficient for the given covariate should just be set to 1 rather than whatever happens to come out of running the specified model to...

Something I noticed while updating `aorsf-bench` in response to https://github.com/bcjaeger/aorsf-bench/pull/7 (👋 @darentsai): in the paper associated with `aorsf-bench`, all benchmarks of variable importance were based on predicted survival probability. Since...

Jaeger, B.C., Edwards, L.J. and Gurka, M.J., 2019. An R 2 statistic for covariance model selection in the linear mixed model. Journal of Applied Statistics, 46(1), pp.164-184.