Open AccessCOMPARISON OF TWO MODELS AND TWO ESTIMATION METHODS FOR CATCH AND EFFORT DATA
Author(s) -
Ludwig D.,
Walters C. J.,
Cooke Justin
Publication year - 1988
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/j.1939-7445.1988.tb00068.x
Subject(s) - randomness , computer science , series (stratigraphy) , estimation , interval (graph theory) , time series , mathematical optimization , mathematics , statistics , econometrics , economics , paleontology , management , combinatorics , biology
We consider the problem of estimating the optimal steady effort level from a time series of catch and effort data, taking account of errors in the observation of the “effective effort” as well as randomness in the stock‐production function. The “total least squares” method ignores the time series nature of the data, while the “approximate likelihood” method takes it into account. We compare estimation schemes based upon these two methods by applying them to artificial data for which the “correct” parameters are known. We use a similar procedure to compare the effectiveness of a “power model” for stock and production with the “Ricker model.” We apply these estimation methods to some sets of real data, and obtain an interval estimate of the optimal effort.