Maximum Likelihood Estimation Strategy for FB4 Model
Source:R/14.2.5-strategy-mle.R
strategy-mle.RdImplements the "mle" FB4 fitting strategy, which estimates the
proportion of maximum consumption (p-value) and its uncertainty by
maximising the log-normal likelihood of observed final weights. Both an R
backend (fit_fb4_mle) and a faster TMB/C++ backend
(execute_mle_tmb) are supported. Confidence intervals are derived
from the Hessian (delta method) and optionally from a likelihood profile
(compute_likelihood_profile).
Value
No return value; this page documents the maximum likelihood estimation strategy functions. See individual function documentation for return values.
References
Deslauriers, D., Chipps, S.R., Breck, J.E., Rice, J.A. and Madenjian, C.P. (2017). Fish Bioenergetics 4.0: An R-based modeling application. Fisheries, 42(11), 586–596. doi:10.1080/03632415.2017.1377558
Kristensen, K., Nielsen, A., Berg, C.W., Skaug, H. and Bell, B.M. (2016). TMB: Automatic differentiation and Laplace approximation. Journal of Statistical Software, 70(5), 1–21. doi:10.18637/jss.v070.i05