Model configuration

Catch data

Enter the unit for catch data in the field above, e.g. "Tonnes".

Abundance Index 1

If you do not enter a month, it will be assumed to be at the beginning of the year. Leave all values blank if you do not have an appropriate index

Abundance Index 2

If you do not enter a month, it will be assumed to be at the beginning of the year. Leave all values blank if you do not have an appropriate index

Abundance Index 3

If you do not enter a month, it will be assumed to be at the beginning of the year. Leave all values blank if you do not have an appropriate index

Abundance Index 4

If you do not enter a month, it will be assumed to be at the beginning of the year. Leave all values blank if you do not have an appropriate index

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Checklist for the acceptance of a SPiCT assessment

Based on the spict guidelines documentation

  1. The assessment converged (fit$opt$convergence equals 0).

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  2. All variance parameters of the model parameters are finite (all(is.finite(fit$sd)) should be TRUE).

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  3. No violation of model assumptions based on one-step-ahead residuals (bias, auto-correlation, normality). This means, that p-values are insignificant (> 0.05), indicated by green titles in the graphs of spictplot.diagnostic(fit). Slight violations of these assumptions do not necessarily invalidate model results.

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Please note that this is a preliminary checklist, you should consult the SPiCt guidelines documentation for a full list of requirements to check.

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References:

Manual for the Stochastic Production model in Continuous Time (SPiCT)

Mildenberger, Tobias K, Casper W Berg, Martin W Pedersen, Alexandros Kokkalis, and J Rasmus Nielsen. 2019. "Time-variant productivity in biomass dynamic models on seasonal and long-term scales." ICES Journal of Marine Science, September. https://doi.org/10.1093/icesjms/fsz154

Pedersen, Martin W., and Casper W. Berg. 2017. "A stochastic surplus production model in continuous time." Fish and Fisheries 18 (2): 226–43. https://doi.org/10.1111/faf.12174