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4. The first proper modelling step is to smooth the biomass and predictors data by combining a `sspm_dataset`, and a `sspm_discrete_boundary`. The user specifies a gam formula with custom smooth terms (see \autoref{tab:formula} for more details). The output is still a `sspm_dataset` object with a `smoothed_data` slot which contains the smoothed predictions for all patches.
The previous code renders to
4. The first proper modelling step is to smooth the biomass and predictors data
by combining a sspm_dataset, and a sspm_discrete_boundary.
The user specifies a gam formula with custom smooth terms (see for more details).
The output is still a sspm_dataset object with a smoothed_data slot which contains
the smoothed predictions for all patches.
where there is no link in the 4th line of the text because \autoref{tab:formula} is not rendering properly.
sspm/vignettes/Package_and_workflow_design.Rmd
Line 27 in 35232f9
The previous code renders to
where there is no link in the 4th line of the text because
\autoref{tab:formula}
is not rendering properly.This issue is part of a review for JOSS, see openjournals/joss-reviews#4724.
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