Version 2.1.13 of RMark is available. You can get the Windows binary or tar.gz file for building on Linux or Mac at
https://drive.google.com/open?id=0B77g1ScdUwVeVU9rUE5lVS1kZ2M&authuser=0I'd appreciate hearing about any tests of the new version of RMark and in particular popan.derived or covariate.predictions. I've tested popan.derived and a few examples of covariate.predictions and all is being computed correctly. But any further testing would be appreciated. The changes should not affect values that don't use mlogit links. Once I'm confident that I've got it right, I'll post to CRAN.
The following is from the package NEWS on the changes made to covariate.predictions
A bug in covariate.predictions was introduced in the change for 2.1.10. Incorrect values were being computed for mlogit parameters when covariate values were not used. popan.derived used that approach and incorrect values resulted for the abundance estimates. Thanks to Leigh Ann Starcevich for reporting this discrepancy. A few other changes were made in covariate.predictions to prevent possible errors with mlogit parameters. If you are making the computations for parameters that use an mlogit link you must use the separate indices argument if you have individual covariate values. If you try to use the data=data.frame(index=...,cov=) approach with mlogit parameters and you have covariate values, the function will stop with an error. Also, if you only include a portion of the indices in an mlogit set, it will also stop and issue an error and will tell you the set of indices that should be included for that mlogit set. If you were allowed to exclude some indices the result would be incorrect because the real parameter values are computed by summing over the entire mlogit set.