Changes in version 2024.1.25 - now ok to have length(models.vars)>1 (was an un-informative error 'length = 2' in coercion to 'logical(1)' in recent versions of R). oChanges in version 2023.8.31 - update un-exported fun arg docs to avoid CRAN NOTE. Changes in version 2021.4.21 - Stop with an error for non-finite predictions. Changes in version 2019.12.3 - test/fix modelSelection for non-monotonic sequences of loss values. Changes in version 2019.11.19 - labelError is OK with model columns that are missing. Changes in version 2019.10.10 - stop with an error for IntervalRegressionCV(., unlogged.outputs). - new args for IntervalRegressionCV including LAPPLY which defaults to future.apply::future_lapply but can be set to base::lapply for debugging. - new notConverging data set and test. - smaller crit before restarting with a larger Lipschitz in IntervalRegressionCV. Changes in version 2019.5.16 - non-strict equality in while(crossing point >= previous breakpoint) to avoid zero-length intervals. - additional tests for modelSelectionFwd. Changes in version 2019.05.15 - Use modelSelectionFwd C algo for modelSelectionC R function. - Fix featureMatrix/labelError/ROChange argument checks, if(logical vector length bigger than 1) was used and is now being checked in R-3.6.0. Changes in version 2019.05.03 - modelSelectionFwd and modelSelectionQuadratic. Changes in version 2019.04.18 - IntervalRegressionCV: informative reg.type undefined error. Changes in version 2019.02.28 - set last_lambda=0 when popping. Changes in version 2019.02.27 - import rather than Depend data.table Changes in version 2018.10.23 - IntervalRegression* stops with an informative error if there are no upper/lower limits. - Remove Remotes/Travis deps. - ROChange now works when there are problems with no thresholds, e.g. the FPR/TPR does not change at all when varying the penalty from Changes in version 2018.09.24 - labelError stops for unrecognized annotations. Changes in version 2018.09.04 - use future.apply::future_lapply. Changes in version 2017.12.08 - remove vignette to pass CRAN check. Changes in version 2017.11.17 - In vignette, remove cghseg since it has memory problems, use Segmentor instead, with trivial 1 segment model when Segmentor fails. - Remove cghseg from example(modelSelectionC). - Don't use fullpage in vignette because that causes a NOTE on CRAN mac. Changes in version 2017.07.12 - try to fix vignette by using cghseg:::segmeanCO instead of Segmentor. Changes in version 2017.07.11 - there is some problem with Segmentor3IsBack on windows, which crashes our vignette re-building in CRAN checks on solaris... not sure why but try to fix via adding tryCatch in vignette. - Add ... passed from IntervalRegressionCV to IntervalRegressionRegularized. Changes in version 2017.06.14 - labelError bugfix and test case for no predicted changes. - Simplify examples -- avoid running Segmentor since this crashes on new versions of R on windows. Changes in version 2017.05.08 - IntervalRegressionCV uses future instead of foreach. Changes in version 2017.05.05 - corrections encountered while preparing tutorial, - - theme_no_space() evaluated at runtime rather than theme_no_space which was evaluated at build time. - - stop with an error if there are models that have the same number of changes -- this prevents problems for changepoint models, but prevents using the code with L1 regularized models (fused lasso). - - stop with an error in targetIntervals if the errors column is not numeric. And return an errors column (the minimum number of incorrect labels). Changes in version 2017.04.11 - prepare for CRAN submission: - convert to src/*.cpp files and register routines. - NULL variables to avoid CRAN checks about global variables. - vignette. - many more user-friendly error messages. - coefficients of IntervalRegression models are now returned on the original scale. Changes in version 2017.03.24 - IntervalRegression S3 class with plot, print, and predict methods. - largestContinuousMinimum C implementation. - more informative error messages when arguments to R functions are not as expected. - check for bigger/smaller data sets in ROChange and labelError. - check for errors in C code and return with non-zero status. Changes in version 2017.01.31 - labelError works when there are more models than labels, and gives an informative error when there are no corresponding models for a given label. Changes in version 2017.01.21 - tests for peak model and for IntervalRegression functions. Changes in version 2017.01.20 - IntervalRegression* functions. Changes in version 2017.01.17 - labelError, targetIntervals, ROChange. Changes in version 2017.01.13 - C solver for linear time modelSelection algorithm, interface via modelSelectionC function. - modelSelectionR function with original quadratic time algorithm in R code. - modelSelection which takes a data.frame as input instead of vectors, and uses modelSelectionC. Changes in version 2017.01.12 - First version.