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SCAMCMC() getADMBCallArgs() getN()
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MCMC settings class |
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SCAPars() stkmodel() n1model() srmodel() fmodel() qmodel() qMod() vmodel() vMod() srPars() srCovar() srFrml() fPars() fCovar() fFrml() qPars() qCovar() qFrml() vPars() vCovar() vFrml() m(<SCAPars>) wt(<SCAPars>) propagate(<SCAPars>) iter(<SCAPars>)
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Model parameters class |
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a4aFit() a4aFit() clock() fitSumm() stock.n(<a4aFit>) harvest(<a4aFit>,<ANY>) catch.n(<a4aFit>) index(<a4aFit>) show(<a4aFit>) logLik(<a4aFit>) iter(<a4aFit>) computeCatchDiagnostics(<a4aFit>)
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S4 class a4aFit |
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computeCatchDiagnostics()
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S4 class a4aFitCatchDiagn |
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a4aFitMCMC() a4aFitMCMC() a4aFitSA(<a4aFitMCMC>) a4aFit(<a4aFitMCMC>) as.mcmc() burnin()
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S4 class a4aFitMCMC |
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residuals(<a4aFit>)
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S4 class a4aFitResiduals |
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a4aFitSA() a4aFitSA() a4aFit(<a4aFitSA>) pars() m(<a4aFitSA>) wt(<a4aFitSA>) qmodel(<a4aFitSA>) fmodel(<a4aFitSA>) srmodel(<a4aFitSA>) n1model(<a4aFitSA>) vmodel(<a4aFitSA>) stkmodel(<a4aFitSA>) show(<a4aFitSA>) submodels(<a4aFitSA>) iter(<a4aFitSA>) a4aFitSAs()
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S4 class a4aFitSA |
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a4aGr() grMod() `grMod<-`() grInvMod() `grInvMod<-`() params(<a4aGr>) `params<-`(<a4aGr>,<FLPar>) distr(<a4aGr>) `distr<-`(<a4aGr>,<character>) vcov(<a4aGr>) `vcov<-`(<a4aGr>,<numeric>)
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Individual growth class |
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a4aInternal()
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Stock assessment model advanced method |
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a4aM() show(<a4aM>) shape() `shape<-`() level() `level<-`() trend() `trend<-`()
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Natural mortality class |
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a4aStkParams() m(<a4aStkParams>) wt(<a4aStkParams>) mat(<a4aStkParams>) fMod() `fMod<-`() n1Mod() `n1Mod<-`() srMod() `srMod<-`() params(<a4aStkParams>) `params<-`(<a4aStkParams>,<FLPar>) coefficients() `coefficients<-`() distr(<a4aStkParams>) `distr<-`(<a4aStkParams>,<character>) vcov(<a4aStkParams>) `vcov<-`(<a4aStkParams>,<array>) propagate(<a4aStkParams>) iter(<a4aStkParams>)
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Stock parameters class |
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`+`(<FLStock>,<a4aFit>) `+`(<FLIndices>,<a4aFit>)
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+ methods |
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getYidx() is.empty() niters() dims(<a4aStkParams>) replaceZeros()
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Assorted methods needed by FLa4a |
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breakpts()
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Breakpoints |
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bubbles(<a4aFitResiduals>,<missing>)
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Bubbles plot of standardized log residuals |
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`formula<-`() coef() `coef<-`()
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coefficients extract and replacement |
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collapseSeasons()
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Collapse seasons |
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defaultFmod() defaultQmod() defaultN1mod() defaultVmod() defaultSRmod()
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Default sub-models |
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a4aSCA()
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deprecated |
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genFLIndex()
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Methods to generate FLIndex objects |
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genFLQuant()
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Methods to generate FLQuant objects |
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genFLStock()
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Methods to generate FLStock objects |
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getADMBHessian() getADMBCovariance()
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Get ADMB Hessian |
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getAcor()
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compute log-correlation matrix |
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getCov()
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Get covariance matrix |
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getK()
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Get K |
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getTPL()
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Get TPL with ADMB code |
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getX()
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Get model matrix |
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hakeGSA7
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hakeGSA7 |
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hakeGSA7.idx
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hakeGSA7.idx |
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index_cd_len
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index_cd_len |
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index_pt_len
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index_pt_len |
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index_sp_len
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index_sp_len |
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l2a()
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Method to convert length-based data to age-based |
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m(<a4aM>)
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natural mortality |
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ma()
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Model averaging (experimental) |
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`*`(<FLStock>,<a4aFitSA>) `*`(<FLStock>,<SCAPars>) `*`(<FLIndices>,<a4aFitSA>) `*`(<FLIndices>,<SCAPars>)
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* methods |
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mvrnorm(<numeric>,<a4aM>,<missing>,<missing>,<missing>,<missing>)
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natural mortality |
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mvrcop(<numeric>,<a4aGr>)
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mvrcop |
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mvrcop()
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Simulation using copula models |
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mvrnorm(<numeric>,<a4aGr>,<ANY>,<ANY>,<ANY>,<ANY>)
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mvrnorm |
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mvrtriangle(<numeric>,<a4aGr>)
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mvrtriangle |
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mvrtriangle()
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Simulation with a copula model and triangular distributions |
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pars2dim()
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Check that the second dimension in params is "iter" |
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plot(<a4aFitResiduals>,<missing>) plot(<a4aFitCatchDiagn>,<missing>)
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Plot of standardized log residuals |
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plot(<a4aFit>,<FLStock>)
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plot for fitted catch-at-age |
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plot(<a4aFit>,<FLIndices>)
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testing |
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predict(<a4aGr>)
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predict for a4aGr |
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predict(<a4aFitSA>) predict(<SCAPars>)
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Predict methods for SCA |
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qqmath(<a4aFitResiduals>,<missing>)
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qqplot of standardized log residuals |
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`range<-`(<a4aM>,<ANY>,<numeric>)
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range for a4aM objects |
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rfLen
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redfish length data |
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rfLen.stk
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rfLen.stk |
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rfTrawl.idx
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rfTrawl.idx |
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rfTrawlJmp.idx
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rfTrawlJmp.idx |
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rfTrawlTrd.idx
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rfTrawlTrd.idx |
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sca()
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Statistical catch-at-age method |
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sca.sa()
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Call sca inside the mp function |
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sep.sa()
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Call a separable SA inside the mp function |
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shake_len
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shake_len |
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simulate()
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Simulation methods for SCA |
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southernHakeLen
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Southern hake length data |
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stdlogres()
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Standardized log residuals |
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submodel() params(<submodel>) sMod() iter(<submodel>) propagate(<submodel>) formula(<submodel>)
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Submodel class |
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submodels() submodels() corBlocks() params(<submodels>) sMod(<submodels>) formula(<submodels>) `corBlocks<-`() `$<-`(<submodels>,<submodel>) `[[<-`(<submodels>,<character>,<missing>) `[[<-`(<submodels>,<numeric>,<missing>) propagate(<submodels>) iter(<submodels>)
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Submodels class |
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vcov(<a4aFitSA>) vcov(<SCAPars>) vcov(<submodels>) vcov(<submodel>) `vcov<-`(<a4aFitSA>,<numeric>) `vcov<-`(<SCAPars>,<numeric>) `vcov<-`(<a4aStkParams>,<numeric>) `vcov<-`(<submodel>,<numeric>) `vcov<-`(<submodel>,<matrix>) `vcov<-`(<submodel>,<array>)
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Variance-covariance matrix |
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wireframe(<FLQuant>,<missing>)
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wireframe plot for FLQuant |