Releases: getzze/RobustModels.jl
Releases · getzze/RobustModels.jl
v0.6.0
RobustModels v0.6.0
Merged pull requests:
- Bump julia v1.6 (#38) (@getzze)
- Use JuliaFormatter (#39) (@getzze)
- Patch GLM (#41) (@getzze)
- fix typo QR (#42) (@getzze)
- Enforce type consistency (#43) (@getzze)
- CompatHelper: add new compat entry for Statistics at version 1, (keep existing compat) (#46) (@github-actions[bot])
- Fix tests for GLM v1.9 (#47) (@getzze)
- Improve coverage (#48) (@getzze)
- Bump to v0.6.0 (#49) (@getzze)
Closed issues:
- appropriate R^2 for fitted models? (#44)
v0.5.0
RobustModels v0.5.0
Closed issues:
Merged pull requests:
- Fix missing type leading to StackOverflow (#17) (@svilupp)
- add test univariate: mean_and_std = (mean, std) (#18) (@getzze)
- add influence function expression in the docs of each estimator (#19) (@getzze)
- create an abstract type AbstractMEstimator to differentiate from non-… (#20) (@getzze)
- prefix new methods by the module defining the function to be extended… (#21) (@getzze)
- add two Catoni loss functions for M-Estimators, CatoniWideLoss and CatoniNarrowLoss (#22) (@getzze)
- add wobs (#23) (@getzze)
- bump compat StatsModels to "0.6, 0.7" (#24) (@getzze)
- remove use of nobs (#25) (@getzze)
- Correct leverage, dof for RidgePred (#26) (@getzze)
- correct Ridge lambda factor 2 and add tests (#27) (@getzze)
- Correct weights, add tests for weights (#28) (@getzze)
- Clean estimator (#30) (@getzze)
- Remove TableRegressionModel wrapper (#31) (@getzze)
- Correct infinite loop (#33) (@getzze)
- Compatibility with julia 1.3 (#34) (@getzze)
- Add GLM.DensePredQR (#35) (@getzze)
- Bump to v0.5 (#36) (@getzze)
v0.4.5
v0.4.4
RobustModels v0.4.4
- Export
hasintercept
function - Correct
nulldeviance
andnullloglikelihood
for models without intercept (JuliaStats/StatsAPI.jl#14). - Update dependencies compat versions (Tulip)
Closed issues:
- Register package (#13)
Merged pull requests:
- CompatHelper: bump compat for Tulip to 0.9, (keep existing compat) (#15) (@github-actions[bot])
v0.4.3
RobustModels v0.4.3
v0.4.2
v0.4.1
v0.4
v0.3
RobustModels v0.3
- API change: estimator type and loss functions are now two different types. Fit a robust model using the new API:
rlm(form, data, MMEstimator{TukeyLoss}(); initial_scale=:L1)
- Robust Ridge regression by specifying the keyword argument
ridgeλ
torlm
:
rlm(form, data, MEstimator{HuberLoss}(); initial_scale=:mad, ridgeλ=0.1)
- Add documentation.