Changelog • midr

midr 0.5.0.904

Updated interpret() to imporove computational efficiency of interpolating parameters.

midr 0.5.0.903

Fixed a bug in interpret.default() that caused inconsistency between “fitted.values” and “residuals.
Updated interpret() to change the automatic determination method of ‘k’.
Added support for “type” suffixes (“_s”: as sequential, “_q”: as qualitative, “_d”: as diverging) in color.theme().
Improved mid.f() to correctly handle vector recycling when an input’s length is 1.
Fixed autoplot.mid.conditional() to avoid doubly evaluation of the “mid” object.

midr 0.5.0.902

Rewrote interpret.formula() to make it able to be called in another function: resolve problems caused by stats::model.frame()
Added new tests for the above feature.
Refined the diverging color theme “midr”.

midr 0.5.0.901

Fix “HCL” color theme to turn it to be a “qualitative” color theme.
Change rounding method of numeric “encoder” objects.
Update an article and example related to color.theme().

midr 0.5.0.900

Enable to change default color themes as options: midr.diverging, midr.qualitative and midr.sequential.
Add the “HCL” color theme and set it as the default qualitative theme.
Fix interpret.formula() to store the evaluated formula in the function call.

midr 0.5.0

CRAN release: 2025-06-23

First release on CRAN.

midr 0.4.9.909

Working paper is now available on arXiv.
Updates for final adjustments.
Some requirements for the ‘x’ argument are removed or relaxed.

midr 0.4.9.908

Fix small bugs including one reported in https://github.com/ryo-asashi/midr/issues/5.
Change the default values of k to avoid singular fits with smaller datasets.

midr 0.4.9.907

interpret() now includes a new verbosity argument for logging.
Fix small bugs.

midr 0.4.9.906

Important: Update the behavior of get.yhat() for classification tasks: If the model returns a matrix or data.frame of class probabilities, by default, get.yhat() returns the probability of not being the base level.

midr 0.4.9.900-0.4.9.905

ggmid.mid.conditional() and plot.mid.conditional() now include a new argument reference, which allows setting the reference point of c-ICE plot to any of the sample points.
color.theme() now includes a new argument, pkg, for package specification.
A new article about “color.theme” objects is added.
A small change of print.mid() and print.mid.conditional().
Important: Update and chane the behavior of interpret() for classification tasks: If y is a factor or character, interpret() convert its base level to 0 and all other levels to 1.
Modify ggmid() and plot.mid() to correct effect plots for factor variables with a catchall level. Additionallym ggmid() now utilize ggplot2::geom_jitter() and allow for adjustable jitter amounts with the jitter argument. Additionally, when data is not explicitly provided, it is now automatically extracted from the function call stored in the "mid" object.
Adjust mid.conditional() and mid.breakdown() so they no longer require explicit data input.
Update terminology.
The color palettes of the khroma package are now available for color.theme().
The default theme for ggmid(type = "data") and plot(type = "data") is changed to a sequential color scheme: “bluescale”.
Add link functions: translogit, transprobit, identity-logistic and identity-gaussian for the interpretation task of classification models.
interpret() now interactively confirms whether a singular fit or exceeding the maximum number of columns is an error.

midr 0.4.3-0.4.8.909

Add mid.ur() to extract uninterpreted ratio (rate) more conveniently.
Modify weighted loss functions to compute deviation-from-mean based losses for one input.
Modify ggmid.mid.breakdown() , ggmid.mid.importance() and plot.mid.breakdown() to improve usability of the functions.
Modify interpret() to add the pred.args argument that can be used to pass optional arguments to the prediction function (pred.fun()).
Add a draft of the article on “the interpretation of classification models”.
Modify interpret() to allow matrices to be used as valid inputs for data (interpret.formula()) and x (interpret.default()).
Add an article on “the interpretation of regression models”.
Define print.encoder() for “encoder” objects to improve usability of the fitted MID models.
Update README.
Change default values of some arguments: e.g. na.action = na.pass of predict.mid().
Fix small bugs of plot.mid.conditional().
Update interpret() to ensure that the value of the argument link is a character string.
Update ggmid.mid.conditional() and plot.mid.conditional(): var.color and the similar arguments can take an expression as input.

midr 0.4.3

midr is in the release process. We will submit the package to CRAN by mid-January 2025 .

Improving usability of graphing functions.
Finalizing code and documentation.
Writing some vignettes. [Submitted to JARIP BULLETIN]