Imports: stats, numDeriv, MASS, Rcpp, graphics, utils, Matrix, parallel
Packaged: 2018-02-12 11:30:56 UTC; laurent.berge

Packaged: 2018-04-26 17:20:19 UTC; laurent.berge

Authors@R: person("Laurent", "Berge", email = "laurent.berge@uni.lu", role = c("aut", "cre"))
Imports: stats, numDeriv, MASS, Rcpp, graphics, utils, Matrix,

Packaged: 2018-09-15 13:50:06 UTC; laurent.berge

Imports: stats, graphics, utils, parallel, Formula, MASS, numDeriv,
can easily be clustered and estimations exported.
Packaged: 2018-09-24 16:13:08 UTC; laurent.berge

Description: Efficient estimation of maximum likelihood models with multiple fixed-effects. Standard-errors can easily and flexibly be clustered and estimations exported.

Packaged: 2018-11-15 16:48:41 UTC; laurent.berge

Packaged: 2019-02-25 09:56:47 UTC; laurent.berge

Packaged: 2019-05-16 08:17:12 UTC; laurent.berge

Packaged: 2019-02-07 11:47:23 UTC; laurent.berge

Authors@R: person("Jaehyuk", "Choi", email = "pyfe@eml.cc", role = c("aut", "cre"))
Description: R implementations of standard financial engineering codes;
vanilla option pricing models such as Black-Scholes, Bachelier, CEV, and

Date: 15 July 2009 version of FEST, R version 2.9.1
Description: Identification of Family Relations using linked markers.
Title: Identification of Family Relations using linked markers
Depends: R (>= 2.4.0), methods, kinship, MASS

Date: 12 April 2010 version of FEST, R version 2.10.1
Depends: R (>= 2.4.0), methods, kinship, MASS, hapsim

Date: 24 August 2010 version of FEST, R version 2.11.0

person("Eldho", "Varghese", email = "eldhoiasri@gmail.com" , role = c("aut", "cre")),
person("Sathianandan", "T V", email = "tvsedpl@gmail.com" , role = "aut"),
person("Jayasankar", "J", email = "jjsankar@gmail.com" , role = "aut"),
person("Reshma", "Gills", email = "reshma1818@gmail.com" , role = "ctb")
Description: Original idea was presented in the reference paper. Varghese et al. (2020, 74(1):35-42) "Bayesian State-space Implementation of Schaefer Production Model for Assessment of Stock Status for Multi-gear Fishery". Marine fisheries governance and management practices are very essential to ensure the sustainability of the marine resources. A widely accepted resource management strategy towards this is to derive sustainable fish harvest levels based on the status of marine fish stock. Various fish stock assessment models that describe the biomass dynamics using time series data on fish catch and fishing effort are generally used for this purpose. In the scenario of complex multi-species marine fishery in which different species are caught by a number of fishing gears and each gear harvests a number of species make it difficult to obtain the fishing effort corresponding to each fish species. Since the capacity of the gears varies, the effort made to catch a resource cannot be considered as the sum of efforts expended by different fishing gears. This necessitates standardisation of fishing effort in unit base.