Changes in version 0.3.18 (2024-06-11) - under new maintainership - various cosmetic/CRAN check updates Changes in version 0.3.15 - 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 respects subset and na.actions arguments for svyglm() models. (#37, h/t Tomasz Żółtak) Changes in version 0.3.13 - Fixed a bug in prediction_glm with the data argument (Issue #32). Changes in version 0.3.12 - Remove mnlogit dependency, as it has been removed from CRAN. Changes in version 0.3.11 - Remove bigFastLm dependency, as it has been removed from CRAN. Changes in version 0.3.10 - Added tests for find_data() and prediction.lm() to check for correct behavior in the presence of missing data (na.action) and subset arguments. (#28) Changes in version 0.3.8 - Provisional support for variances of average predictions for GLMs. (#17) - Added an example dataset, margex, borrowed from Stata's identically named data. Changes in version 0.3.7 - 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 calls summary(prediction(...)). - All methods now return additional attributes. Changes in version 0.3.6 (2018-05-22) - Small fixes for failing CRAN checks. (#25) - Remove prediction.bigglm() method (from biglm) due to failing tests. (#25) Changes in version 0.3.5 - Fixed a bug that required specifying stats::poly() rather than just poly() in model formulae. (#22) Changes in version 0.3.4 - Added prediction.glmnet() method for "glmnet" objects from glmnet. (#1) Changes in version 0.3.3 - prediction.merMod() gains an re.form argument to pass forward to predict.merMod(). Changes in version 0.3.2 (2018-04-12) - Fix typo in "speedglm" that was overwriting "glm" method. Changes in version 0.3.0 - CRAN release. Changes in version 0.2.11 - 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) Changes in version 0.2.10 - 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) Changes in version 0.2.9 - Added prediction.speedglm() and prediction.speedlm() methods for "speedglm" and "speedlm" objects from speedglm. (#1) - Added prediction.bigLm() method for "bigLm" objects from bigFastlm. (#1) - Added prediction.biglm() and prediction.bigglm() methods for "biglm" and "bigglm" objects from biglm, including those based by "ffdf" from ff. (#1) Changes in version 0.2.8 - Changed internal behavior of build_datalist(). The function now returns an an at_specification attribute, which is a data frame representation of the at argument. Changes in version 0.2.6 - Due to a change in gam_1.15, prediction.gam() is now prediction.Gam() for "Gam" objects from gam. (#1) - Added prediction.train() method for "train" objects from caret. (#1) Changes in version 0.2.5 - The at argument in build_datalist() now accepts a data frame of combinations for limiting the set of levels. Changes in version 0.2.3 - Most prediction() methods gain a (experimental) calculate_se argument, which regulates whether to calculate standard errors for predictions. Setting to FALSE can improve performance if they are not needed. - build_datalist() gains an as.data.frame argument, which - if TRUE - returns a stacked data frame rather than a list. This argument is now used internally in most prediction() functions in an effort to improve performance. (#18) Changes in version 0.2.2 - 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 when at != NULL. Changes in version 0.2.1 - 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) Changes in version 0.2.0 (2017-04-19) - CRAN Release. - Added mean_or_mode.data.frame() and median_or_mode.data.frame() methods. Changes in version 0.1.17 - 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(). Changes in version 0.1.16 - Added prediction.plm() method for "plm" objects from plm. (#1) Changes in version 0.1.15 - Expanded test suite considerably and updated CONTRIBUTING.md to reflect expected test-driven development. - A few small code tweaks and bug fixes resulting from the updated test suite. Changes in version 0.1.14 - 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) Changes in version 0.1.13 - Added a category argument to prediction() 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 at argument to prediction() methods. (#13) - Made mean_or_mode() and median_or_mode() S3 generics. - Fixed a bug in mean_or_mode() and median_or_mode() where incorrect factor levels were being returned. Changes in version 0.1.12 - 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 the subset argument in an original model call. (#15) - find_data() now respects the na.action argument 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. Changes in version 0.1.11 (2017-03-22) - build_datalist() now returns at value combinations as a list. Changes in version 0.1.10 (2017-03-01) - Added prediction.nnet() method for "nnet" and "multinom" objects from nnet. (#1) Changes in version 0.1.9 - prediction() methods now return the value of data as 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() and prediction.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. Changes in version 0.1.8 - Added prediction() and find_data() methods for "crch" "hxlr" objects from crch. (#4, h/t Carl Ganz) Changes in version 0.1.7 - Added prediction() and find_data() methods for "merMod" objects from lme4. (#1) Changes in version 0.1.6 - 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. Changes in version 0.1.5 - Added prediction.svm() method for objects of class "svm" from e1071. (#1) - Fixed a bug in prediction.polr() when attempting to pass a type argument, which is always ignored. A warning is now issued when attempting to override this. Changes in version 0.1.4 - Added mean_or_mode() and median_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". Changes in version 0.1.3 - find_data() is now a generic, methods for "lm", "glm", and "svyglm" classes. (#2, h/t Carl Ganz) Changes in version 0.1.2 - Added support for "svyglm" class from the survey package. (#1) - Added tentative support for "clm" class from the ordinal package. (#1) Changes in version 0.1.0 - Initial package released.