# prediction 0.3.13 * Fixed a bug in `prediction_glm` with the `data` argument (Issue #32). # prediction 0.3.12 * Remove mnlogit dependency, as it has been removed from CRAN. # prediction 0.3.11 * Remove bigFastLm dependency, as it has been removed from CRAN. # prediction 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) # prediction 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. # prediction 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. # prediction 0.3.6 * Small fixes for failing CRAN checks. (#25) * Remove `prediction.bigglm()` method (from **biglm**) due to failing tests. (#25) # prediction 0.3.5 * Fixed a bug that required specifying `stats::poly()` rather than just `poly()` in model formulae. (#22) # prediction 0.3.4 * Added `prediction.glmnet()` method for "glmnet" objects from **glmnet**. (#1) # prediction 0.3.3 * `prediction.merMod()` gains an `re.form` argument to pass forward to `predict.merMod()`. # prediction 0.3.2 * Fix typo in "speedglm" that was overwriting "glm" method. # prediction 0.3.0 * CRAN release. # prediction 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) # prediction 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) # prediction 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) # prediction 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. # prediction 0.2.6 * Due to a change in gam_1.15, `prediction.gam()` is now `prediction.Gam()` for "Gam" objects from **gam**. (#1) # prediction 0.2.6 * Added `prediction.train()` method for "train" objects from **caret**. (#1) # prediction 0.2.5 * The `at` argument in `build_datalist()` now accepts a data frame of combinations for limiting the set of levels. # prediction 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. # prediction 0.2.3 * `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) # prediction 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`. # prediction 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) # prediction 0.2.0 * CRAN Release. * Added `mean_or_mode.data.frame()` and `median_or_mode.data.frame()` methods. # prediction 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()`. # prediction 0.1.16 * Added `prediction.plm()` method for "plm" objects from **plm**. (#1) # prediction 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. # prediction 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) # prediction 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. # prediction 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. # prediction 0.1.11 * `build_datalist()` now returns `at` value combinations as a list. # prediction 0.1.10 * Added `prediction.nnet()` method for "nnet" and "multinom" objects from **nnet**. (#1) # prediction 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. # prediction 0.1.8 * Added `prediction()` and `find_data()` methods for `"crch"` `"hxlr"` objects from **crch**. (#4, h/t Carl Ganz) # prediction 0.1.7 * Added `prediction()` and `find_data()` methods for `"merMod"` objects from **lme4**. (#1) # prediction 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. # prediction 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. # prediction 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". # prediction 0.1.3 * `find_data()` is now a generic, methods for "lm", "glm", and "svyglm" classes. (#2, h/t Carl Ganz) # prediction 0.1.2 * Added support for "svyglm" class from the **survey** package. (#1) * Added tentative support for "clm" class from the **ordinal** package. (#1) # prediction 0.1.0 * Initial package released.