- under new maintainership
- various cosmetic/CRAN check updates
build_datalist()now works correctly with data.table datasets. (#34, #35, h/t Dan Schrage)build_datalist()dropped factor levels when replacing a factor variable. (#39, h/t Tomasz Żółtak)find_data()now respectssubsetandna.actionsarguments forsvyglm()models. (#37, h/t Tomasz Żółtak)
- Fixed a bug in
prediction_glmwith thedataargument (Issue #32).
- Remove mnlogit dependency, as it has been removed from CRAN.
- Remove bigFastLm dependency, as it has been removed from CRAN.
- Added tests for
find_data()andprediction.lm()to check for correct behavior in the presence of missing data (na.action) andsubsetarguments. (#28)
- Provisional support for variances of average predictions for GLMs. (#17)
- Added an example dataset,
margex, borrowed from Stata's identically named data.
summary(prediction(...))now reports variances of average predictions, along with test statistics, p-values, and confidence intervals, where supported. (#17)- Added a function
prediction_summary()which simply callssummary(prediction(...)). - All methods now return additional attributes.
- Small fixes for failing CRAN checks. (#25)
- Remove
prediction.bigglm()method (from biglm) due to failing tests. (#25)
- Fixed a bug that required specifying
stats::poly()rather than justpoly()in model formulae. (#22)
- Added
prediction.glmnet()method for "glmnet" objects from glmnet. (#1)
prediction.merMod()gains anre.formargument to pass forward topredict.merMod().
- Fix typo in "speedglm" that was overwriting "glm" method.
- CRAN release.
- Added
prediction.glmML()method for "glimML" objects from aod. (#1) - Added
prediction.glmQL()method for "glimQL" objects from aod. (#1) - Added
prediction.truncreg()method for "truncreg" objects from truncreg. (#1) - Noted implicit support for "tobit" objects from AER. (#1)
- Added
prediction.bruto()method for "bruto" objects from mda. (#1) - Added
prediction.fda()method for "fda" objects from mda. (#1) - Added
prediction.mars()method for "mars" objects from mda. (#1) - Added
prediction.mda()method for "mda" objects from mda. (#1) - Added
prediction.polyreg()method for "polyreg" objects from mda. (#1)
- Added
prediction.speedglm()andprediction.speedlm()methods for "speedglm" and "speedlm" objects from speedglm. (#1) - Added
prediction.bigLm()method for "bigLm" objects from bigFastlm. (#1) - Added
prediction.biglm()andprediction.bigglm()methods for "biglm" and "bigglm" objects from biglm, including those based by"ffdf"from ff. (#1)
- Changed internal behavior of
build_datalist(). The function now returns an anat_specificationattribute, which is a data frame representation of theatargument.
- Due to a change in gam_1.15,
prediction.gam()is nowprediction.Gam()for "Gam" objects from gam. (#1)
- Added
prediction.train()method for "train" objects from caret. (#1)
- The
atargument inbuild_datalist()now accepts a data frame of combinations for limiting the set of levels.
- Most
prediction()methods gain a (experimental)calculate_seargument, which regulates whether to calculate standard errors for predictions. Setting toFALSEcan improve performance if they are not needed.
build_datalist()gains anas.data.frameargument, which - ifTRUE- returns a stacked data frame rather than a list. This argument is now used internally in mostprediction()functions in an effort to improve performance. (#18)
- Expanded test suite scope and fixed a few small bugs.
- Added a
summary.prediction()method to interact with the average predicted values that are printed whenat != NULL.
- Added
prediction.knnreg()method for "knnreg" objects from caret. (#1) - Added
prediction.gausspr()method for "gausspr" objects from kernlab. (#1) - Added
prediction.ksvm()method for "ksvm" objects from kernlab. (#1) - Added
prediction.kqr()method for "kqr" objects from kernlab. (#1) - Added
prediction.earth()method for "earth" objects from earth. (#1) - Added
prediction.rpart()method for "rpart" objects from rpart. (#1)
- CRAN Release.
- Added
mean_or_mode.data.frame()andmedian_or_mode.data.frame()methods.
- Added
prediction.zeroinfl()method for "zeroinfl" objects from pscl. (#1) - Added
prediction.hurdle()method for "hurdle" objects from pscl. (#1) - Added
prediction.lme()method for "lme" and "nlme" objects from nlme. (#1) - Documented
prediction.merMod().
- Added
prediction.plm()method for "plm" objects from plm. (#1)
- Expanded test suite considerably and updated
CONTRIBUTING.mdto reflect expected test-driven development. - A few small code tweaks and bug fixes resulting from the updated test suite.
- Added
prediction.mnp()method for "mnp" objects from MNP. (#1) - Added
prediction.mnlogit()method for "mnlogit" objects from mnlogit. (#1) - Added
prediction.gee()method for "gee" objects from gee. (#1) - Added
prediction.lqs()method for "lqs" objects from MASS. (#1) - Added
prediction.mca()method for "mca" objects from MASS. (#1) - Noted (built-in) support for "brglm" objects from brglm via the
prediction.glm()method. (#1)
- Added a
categoryargument toprediction()methods for models of multilevel outcomes (e.g., ordered probit, etc.) to be dictate which level is expressed as the"fitted"column. (#14) - Added an
atargument toprediction()methods. (#13) - Made
mean_or_mode()andmedian_or_mode()S3 generics. - Fixed a bug in
mean_or_mode()andmedian_or_mode()where incorrect factor levels were being returned.
- Added
prediction.princomp()method for "princomp" objects from stats. (#1) - Added
prediction.ppr()method for "ppr" objects from stats. (#1) - Added
prediction.naiveBayes()method for "naiveBayes" objects from e1071. (#1) - Added
prediction.rlm()method for "rlm" objects from MASS. (#1) - Added
prediction.qda()method for "qda" objects from MASS. (#1) - Added
prediction.lda()method for "lda" objects from MASS. (#1) find_data()now respects thesubsetargument in an original model call. (#15)find_data()now respects thena.actionargument in an original model call. (#15)find_data()now gracefully fails when a model is specified without a formula. (#16)prediction()methods no longer add a "fit" or "se.fit" class to any columns. Fitted values are identifiable by the column name only.
build_datalist()now returnsatvalue combinations as a list.
- Added
prediction.nnet()method for "nnet" and "multinom" objects from nnet. (#1)
prediction()methods now return the value ofdataas part of the response data frame. (#8, h/t Ben Whalley)- Slight change to
find_data()methods for"crch"and"hxlr". (#5) - Added
prediction.glmx()andprediction.hetglm()methods for "glmx" and "hetglm" objects from glmx. (#1) - Added
prediction.betareg()method for "betareg" objects from betareg. (#1) - Added
prediction.rq()method for "rq" objects from quantreg. (#1) - Added
prediction.gam()method for "gam" objects from gam. (#1) - Expanded basic test suite.
- Added
prediction()andfind_data()methods for"crch""hxlr"objects from crch. (#4, h/t Carl Ganz)
- Added
prediction()andfind_data()methods for"merMod"objects from lme4. (#1)
- Moved the
seq_range()function from margins to prediction. - Moved the
build_datalist()function from margins to prediction. This will simplify the ability to calculate arbitrary predictions.
- Added
prediction.svm()method for objects of class"svm"from e1071. (#1) - Fixed a bug in
prediction.polr()when attempting to pass atypeargument, which is always ignored. A warning is now issued when attempting to override this.
- Added
mean_or_mode()andmedian_or_mode()functions, which provide a simple way to aggregate a variable of factor or numeric type. (#3) - Added
prediction()methods for various time-series model classes: "ar", "arima0", and "Arima".
find_data()is now a generic, methods for "lm", "glm", and "svyglm" classes. (#2, h/t Carl Ganz)
- Added support for "svyglm" class from the survey package. (#1)
- Added tentative support for "clm" class from the ordinal package. (#1)
- Initial package released.