Known-Biomass Production Model (KBPM)

Application of a Known Biomass Production Model (KBPM): (1) the fitting of KBPM to each stock; (2) the estimation of the effects of environmental variability; (3) the retrospective analysis to identify regime shifts; (4) the estimation of forecasts. For more details see Schaefer (1954) < https://www.iattc.org/GetAttachment/62d510ee-13d0-40f2-847b-0fde415476b8/Vol-1-No-2-1954-SCHAEFER,-MILNER-B-_Some-aspects-of-the-dynamics-of-populations-important-to-the-management-of-the-commercial-marine-fisheries.pdf>, Pella and Tomlinson (1969) < https://www.iattc.org/GetAttachment/9865079c-6ee7-40e2-9e30-c4523ff81ddf/Vol-13-No-3-1969-PELLA,-JEROME-J-,-and-PATRICK-K-TOMLINSON_A-generalized-stock-production-model.pdf> and MacCall (2002) .

knobi

Authors: Paz, A., Cousido-Rocha, M., Pennino, M.G., Cerviño, S.

Application of a KBPM (Known Biomass Production Model): (1) the fitting of KBPM to each stock; (2) the estimation of the effects of environmental variability; (3) the retrospective analysis to identify regime shifts; (4) the estimation of forecasts.

First step is to install devtools package using install.packages("devtools").

There are two options for installing our package:

1. Version with vignettes

devtools::install_github("anxopaz/knobi",build_vignettes = TRUE)

This option needs to install previously the following packages:

install.packages( c("corrplot", "ggplot2",  "gridExtra", "grDevices",  "optimx", "plot3D", "dplyr", "tidyr"))

2. Version without vignettes

devtools::install_github("anxopaz/knobi")

This is a faster option.

It is recommended to restart R after the installation of the package.