# Configuration saved: Mon Jan 9 14:29:49 2023 # # Where a matrix is specified rows corresponds to fleets and columns to ages. # Same number indicates same parameter used # Numbers (integers) starts from zero and must be consecutive # Negative numbers indicate that the parameter is not included in the model # $minAge # The minimium age class in the assessment 2 $maxAge # The maximum age class in the assessment 10 $maxAgePlusGroup # Is last age group considered a plus group for each fleet (1 yes, or 0 no). 1 0 $keyLogFsta # Coupling of the fishing mortality states processes for each age (normally only # the first row (= fleet) is used). # Sequential numbers indicate that the fishing mortality is estimated individually # for those ages; if the same number is used for two or more ages, F is bound for # those ages (assumed to be the same). Binding fully selected ages will result in a # flat selection pattern for those ages. 0 1 2 3 4 5 6 7 7 -1 -1 -1 -1 -1 -1 -1 -1 -1 $corFlag # Correlation of fishing mortality across ages (0 independent, 1 compound symmetry, # 2 AR(1), 3 separable AR(1). # 0: independent means there is no correlation between F across age # 1: compound symmetry means that all ages are equally correlated; # 2: AR(1) first order autoregressive - similar ages are more highly correlated than # ages that are further apart, so similar ages have similar F patterns over time. # if the estimated correlation is high, then the F pattern over time for each age # varies in a similar way. E.g if almost one, then they are parallel (like a # separable model) and if almost zero then they are independent. # 3: Separable AR - Included for historic reasons . . . more later 0 $keyLogFpar # Coupling of the survey catchability parameters (nomally first row is # not used, as that is covered by fishing mortality). -1 -1 -1 -1 -1 -1 -1 -1 -1 0 1 2 3 4 -1 -1 -1 -1 $keyQpow # Density dependent catchability power parameters (if any). -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 $keyVarF # Coupling of process variance parameters for log(F)-process (Fishing mortality # normally applies to the first (fishing) fleet; therefore only first row is used) 0 0 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 -1 $keyVarLogN # Coupling of the recruitment and survival process variance parameters for the # log(N)-process at the different ages. It is advisable to have at least the first age # class (recruitment) separate, because recruitment is a different process than # survival. 0 1 1 1 1 1 1 1 1 $keyVarObs # Coupling of the variance parameters for the observations. # First row refers to the coupling of the variance parameters for the catch data # observations by age # Second and further rows refers to coupling of the variance parameters for the # index data observations by age 0 1 2 2 2 2 2 2 2 3 4 5 5 5 -1 -1 -1 -1 $obsCorStruct # Covariance structure for each fleet ("ID" independent, "AR" AR(1), or "US" for unstructured). | Possible values are: "ID" "AR" "US" "ID" "AR" $keyCorObs # Coupling of correlation parameters can only be specified if the AR(1) structure is chosen above. # NA's indicate where correlation parameters can be specified (-1 where they cannot). #2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 NA NA NA NA NA NA NA NA 0 0 0 0 -1 -1 -1 -1 $stockRecruitmentModelCode # Stock recruitment code (0 for plain random walk, 1 for Ricker, 2 for Beverton-Holt, 3 piece-wise constant, 61 for segmented regression/hockey stick, 62 for AR(1), 63 for bent hyperbola / smooth hockey stick, 64 for power function with degree < 1, 65 for power function with degree > 1, 66 for Shepher, 67 for Deriso, 68 for Saila-Lorda, 69 for sigmoidal Beverton-Holt, 90 for CMP spline, 91 for more flexible spline, and 92 for most flexible spline). 0 $noScaledYears # Number of years where catch scaling is applied. 0 $keyScaledYears # A vector of the years where catch scaling is applied. $keyParScaledYA # A matrix specifying the couplings of scale parameters (nrow = no scaled years, ncols = no ages). $fbarRange # lowest and higest age included in Fbar 5 8 $keyBiomassTreat # To be defined only if a biomass survey is used (0 SSB index, 1 catch index, 2 FSB index, 3 total catch, 4 total landings and 5 TSB index). -1 -1 $obsLikelihoodFlag # Option for observational likelihood | Possible values are: "LN" "ALN" "LN" "LN" $fixVarToWeight # If weight attribute is supplied for observations this option sets the treatment (0 relative weight, 1 fix variance to weight). 0 $fracMixF # The fraction of t(3) distribution used in logF increment distribution 0 $fracMixN # The fraction of t(3) distribution used in logN increment distribution (for each age group) 0 0 0 0 0 0 0 0 0 $fracMixObs # A vector with same length as number of fleets, where each element is the fraction of t(3) distribution used in the distribution of that fleet 0 0 0 $constRecBreaks # Vector of break years between which recruitment is at constant level. The break year is included in the left interval. (This option is only used in combination with stock-recruitment code 3) $predVarObsLink # Coupling of parameters used in a prediction-variance link for observations. -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 NA NA NA NA $hockeyStickCurve # 20 $stockWeightModel # Integer code describing the treatment of stock weights in the model (0 use as known, 1 use as observations to inform stock weight process (GMRF with cohort and within year correlations)) 1 $keyStockWeightMean # Coupling of stock-weight process mean parameters (not used if stockWeightModel==0) 0 1 2 3 4 5 6 7 8 $keyStockWeightObsVar # Coupling of stock-weight observation variance parameters (not used if stockWeightModel==0) 0 0 0 0 0 0 0 0 0 $catchWeightModel # Integer code describing the treatment of catch weights in the model (0 use as known, 1 use as observations to inform catch weight process (GMRF with cohort and within year correlations)) 1 $keyCatchWeightMean # Coupling of catch-weight process mean parameters (not used if catchWeightModel==0) 0 1 2 3 4 5 6 7 8 $keyCatchWeightObsVar # Coupling of catch-weight observation variance parameters (not used if catchWeightModel==0) 0 0 0 0 0 0 0 0 0 $matureModel # Integer code describing the treatment of proportion mature in the model (0 use as known, 1 use as observations to inform proportion mature process (GMRF with cohort and within year correlations on logit(proportion mature))) 0 $keyMatureMean # Coupling of mature process mean parameters (not used if matureModel==0) NA NA NA NA NA NA NA NA NA $mortalityModel # Integer code describing the treatment of natural mortality in the model (0 use as known, 1 use as observations to inform natural mortality process (GMRF with cohort and within year correlations)) 0 $keyMortalityMean # NA NA NA NA NA NA NA NA NA $keyMortalityObsVar # Coupling of natural mortality observation variance parameters (not used if mortalityModel==0) NA NA NA NA NA NA NA NA NA $keyXtraSd # An integer matrix with 4 columns (fleet year age coupling), which allows additional uncertainty to be estimated for the specified observations 1 2000 2 0 1 2001 2 0 1 2002 2 0 1 2003 2 0 1 2004 2 0 1 2005 2 0 1 2006 2 0 1 2007 2 0 1 2008 2 0 1 2009 2 0 1 2010 2 0 1 2000 3 0 1 2001 3 0 1 2002 3 0 1 2003 3 0 1 2004 3 0 1 2005 3 0 1 2006 3 0 1 2007 3 0 1 2008 3 0 1 2009 3 0 1 2010 3 0 1 2000 4 0 1 2001 4 0 1 2002 4 0 1 2003 4 0 1 2004 4 0 1 2005 4 0 1 2006 4 0 1 2007 4 0 1 2008 4 0 1 2009 4 0 1 2010 4 0 1 2000 5 0 1 2001 5 0 1 2002 5 0 1 2003 5 0 1 2004 5 0 1 2005 5 0 1 2006 5 0 1 2007 5 0 1 2008 5 0 1 2009 5 0 1 2010 5 0 1 2000 6 0 1 2001 6 0 1 2002 6 0 1 2003 6 0 1 2004 6 0 1 2005 6 0 1 2006 6 0 1 2007 6 0 1 2008 6 0 1 2009 6 0 1 2010 6 0 1 2000 7 0 1 2001 7 0 1 2002 7 0 1 2003 7 0 1 2004 7 0 1 2005 7 0 1 2006 7 0 1 2007 7 0 1 2008 7 0 1 2009 7 0 1 2010 7 0 1 2000 8 0 1 2001 8 0 1 2002 8 0 1 2003 8 0 1 2004 8 0 1 2005 8 0 1 2006 8 0 1 2007 8 0 1 2008 8 0 1 2009 8 0 1 2010 8 0 1 2000 9 0 1 2001 9 0 1 2002 9 0 1 2003 9 0 1 2004 9 0 1 2005 9 0 1 2006 9 0 1 2007 9 0 1 2008 9 0 1 2009 9 0 1 2010 9 0 1 2000 10 0 1 2001 10 0 1 2002 10 0 1 2003 10 0 1 2004 10 0 1 2005 10 0 1 2006 10 0 1 2007 10 0 1 2008 10 0 1 2009 10 0 1 2010 10 0 2 2000 2 1 2 2001 2 1 2 2002 2 1 2 2003 2 1 2 2004 2 1 2 2005 2 1 2 2006 2 1 2 2007 2 1 2 2008 2 1 2 2009 2 1 2 2010 2 1 2 2000 3 1 2 2001 3 1 2 2002 3 1 2 2003 3 1 2 2004 3 1 2 2005 3 1 2 2006 3 1 2 2007 3 1 2 2008 3 1 2 2009 3 1 2 2010 3 1 2 2000 4 1 2 2001 4 1 2 2002 4 1 2 2003 4 1 2 2004 4 1 2 2005 4 1 2 2006 4 1 2 2007 4 1 2 2008 4 1 2 2009 4 1 2 2010 4 1 2 2000 5 1 2 2001 5 1 2 2002 5 1 2 2003 5 1 2 2004 5 1 2 2005 5 1 2 2006 5 1 2 2007 5 1 2 2008 5 1 2 2009 5 1 2 2010 5 1 2 2000 6 1 2 2001 6 1 2 2002 6 1 2 2003 6 1 2 2004 6 1 2 2005 6 1 2 2006 6 1 2 2007 6 1 2 2008 6 1 2 2009 6 1 2 2010 6 1