New MARK Version June 2014

June, 2014 Version 8.0 California Sea Lion
235. The N parameter in all of the closed captures data types and robust design derivatives has been changed to be labeled f0 to prevent users from mistakenly thinking setting the N parameters equal is evaluating this hypothesis. N is still provided as a derived parameter.
236. The random effects version of the Huggins estimator has been added for closed captures, robust designs, closed multi-state, and Pradel robust designs. The estimator uses Gauss-Hermite quadrature to integrate out individual random effects on detection probability, p. Population estimates are provided as derived parameters based on the estimated mean detection probability.
237. The Fletcher chat estimator (Fletcher 2012) has been added to the full output file, and also for collection by the simulator. This estimator requires knowing the total number of possible encounter histories, which can be problematic when parameter estimates preclude some histories. Examples of this problem are p = 0 in the CJS data type, or transition probabilities (psi) fixed to 0 or 1 in multi-state models. Other similar problems are caused by dots in the encounter history, or losses on capture.
238. The random effects version of the occupancy estimator has been added for single-season occupancy, and multi-season robust designs. The estimator uses Gauss-Hermite quadrature to integrate out individual random effects on detection probability, p.
Gary
235. The N parameter in all of the closed captures data types and robust design derivatives has been changed to be labeled f0 to prevent users from mistakenly thinking setting the N parameters equal is evaluating this hypothesis. N is still provided as a derived parameter.
236. The random effects version of the Huggins estimator has been added for closed captures, robust designs, closed multi-state, and Pradel robust designs. The estimator uses Gauss-Hermite quadrature to integrate out individual random effects on detection probability, p. Population estimates are provided as derived parameters based on the estimated mean detection probability.
237. The Fletcher chat estimator (Fletcher 2012) has been added to the full output file, and also for collection by the simulator. This estimator requires knowing the total number of possible encounter histories, which can be problematic when parameter estimates preclude some histories. Examples of this problem are p = 0 in the CJS data type, or transition probabilities (psi) fixed to 0 or 1 in multi-state models. Other similar problems are caused by dots in the encounter history, or losses on capture.
238. The random effects version of the occupancy estimator has been added for single-season occupancy, and multi-season robust designs. The estimator uses Gauss-Hermite quadrature to integrate out individual random effects on detection probability, p.
Gary