Changes in version 2024.9.3

- change error() to Rf_error() for R-4.5 R_NO_REMAP.

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).

Changes 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.