RMark version 2.2.7 on CRAN

posts related to the RMark library, which may not be of general interest to users of 'classic' MARK

RMark version 2.2.7 on CRAN

Postby jlaake » Thu Nov 07, 2019 2:16 pm

A new version was released to CRAN earlier this week. Below is a list of changes and additions.

RMark 2.2.7 (4 November 2019)

NEW FEATURES

* added Paradise_shelduck example of multistate live-dead model courtesy of Richard Barker.

* added capability to set subtract.stratum for pi and subtract.events for Delta with HidMarkov models. The subtract.stratum for pi has a value for each event and subtract.events for Delta has a value for each stratum that can either be the stratum value or one of the events.

* added support for RDMultScalOcc model. Thanks to Connor Wood and Gary White for providing examples to test. Connor added an example. ?RDMultScalOcc

* added support for RDMSOccupancy model. Thanks to Wendy Lanier for help in figuring out the model parameters and providing a test example.

* added a check.model argument to make.mark.model. This argument is primarily for my use when adding models. It checks to make sure ordering of PIMs is consistent with the design data order. I had the order incorrect initially when adding the RDMSOccupancy model and it made me realize I should have this in the code. No problems were discovered in running all of the examples in the package. I have set the default value to FALSE but if you want to check a model type that doesn't have an example in the package, set to TRUE. Don't panic if it flags an error as I did when I first ran it. The code doing the testing may not be perfect and was initially giving false errors. But please do let me know if you encounter any problems.

* alpha argument in covariate.predictions was originally intended just for mata-wald confidence intervals but it has been extended to be used with regular confidence intervals as well. The value 1.96 has been replaced with qnorm(1-alpha) and the default value of alpha=0.025 will give the same(very close) result as previous use of 1.96 for 95% confidence intervals.

CHANGES
* Jay Rotella updated the mallard example to use mark.wrapper approach to fitting a set of models.
jlaake
 
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