Correct itemize brackets in documentation and href + update OptionsBi…

…gboss documentation and authors
biomodhub · Jan 23, 2024 · 2acd801 · 2acd801
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -9,22 +9,23 @@ Authors@R: c(person("Wilfried", "Thuiller", role = c("aut")
              person("Maya", "Gueguen", role = c("aut", "cre")
                     , email = "[email protected]"),
              person("Robin", "Engler", role = "aut"),
-             person("Frank", "Breiner", role = "aut"
-                    , email = "[email protected]"),
+             person("Frank", "Breiner", role = "aut"),
              person("Bruno", "Lafourcade", role = "aut"),
-             person("Remi", "Patin", role = "aut"
-                    , email = "[email protected]"))
+             person("Remi", "Patin", role = "aut"),
+             person("Helene", "Blancheteau", role = "aut"
+                    , email = "[email protected]"))
 Author: Wilfried Thuiller [aut],
     Damien Georges [aut],
     Maya Gueguen [aut, cre],
     Robin Engler [aut],
     Frank Breiner [aut],
     Bruno Lafourcade [aut],
-    Remi Patin [aut]
+    Remi Patin [aut],
+    Helene Blancheteau [aut]
 Maintainer: Maya Gueguen <[email protected]>
-Contact: Wilfried Thuiller <[email protected]>, Damien Georges
-    <[email protected]>, Maya Gueguen <[email protected]>, 
-    Remi Patin <remi.patin@univ-grenoble-alpes.fr>
+Contact: Wilfried Thuiller <[email protected]>, 
+    Maya Gueguen <[email protected]>, 
+    Helene Blancheteau <helene.blancheteau@univ-grenoble-alpes.fr>
 BugReports: https://github.com/biomodhub/biomod2/issues
 URL: https://biomodhub.github.io/biomod2/
 Description: Functions for species distribution modeling, calibration and evaluation, 

diff --git a/R/BIOMOD_EnsembleForecasting.R b/R/BIOMOD_EnsembleForecasting.R
@@ -93,16 +93,16 @@
 ##' 
 ##' \code{...} can take the following values :
 ##' \itemize{
-##'   \item{\code{on_0_1000} : }{a \code{logical} value defining whether \code{0 - 1} 
-##'   probabilities are to be converted to \code{0 - 1000} scale to save memory on backup}
-##'   \item{\code{do.stack} : }{a \code{logical} value defining whether all projections are to be 
+##'   \item \code{on_0_1000} : a \code{logical} value defining whether \code{0 - 1} 
+##'   probabilities are to be converted to \code{0 - 1000} scale to save memory on backup
+##'   \item \code{do.stack} : a \code{logical} value defining whether all projections are to be 
 ##'   saved as one \code{SpatRaster} object or several \code{SpatRaster} files (\emph{the 
-##'   default if projections are too heavy to be all loaded at once in memory})}
-##'   \item{\code{keep.in.memory} : }{a \code{logical} value defining whether all projections are 
-##'   to be kept loaded at once in memory, or only links pointing to hard drive are to be returned}
-##'   \item{\code{output.format} : }{a \code{character} value corresponding to the projections 
+##'   default if projections are too heavy to be all loaded at once in memory})
+##'   \item \code{keep.in.memory} : a \code{logical} value defining whether all projections are 
+##'   to be kept loaded at once in memory, or only links pointing to hard drive are to be returned
+##'   \item \code{output.format} : a \code{character} value corresponding to the projections 
 ##'   saving format on hard drive, must be either \code{.grd}, \code{.img}, \code{.tif} or \code{.RData} (the 
-##'   default if \code{new.env} is given as \code{matrix} or \code{data.frame})}
+##'   default if \code{new.env} is given as \code{matrix} or \code{data.frame})
 ##' }
 ##' 
 ##' 

diff --git a/R/BIOMOD_EnsembleModeling.R b/R/BIOMOD_EnsembleModeling.R
@@ -122,15 +122,15 @@
 ##'   \code{\link{BIOMOD_Modeling}} function can be combined in 5 different ways to obtain 
 ##'   ensemble models :
 ##'   \itemize{
-##'     \item{\code{PA+run} : }{each combination of pseudo-absence and repetition 
-##'     datasets is done, \emph{merging} algorithms together}
-##'     \item{\code{PA+algo} : }{each combination of pseudo-absence and algorithm datasets 
-##'     is done, \emph{merging} repetitions together}
-##'     \item{\code{PA} : }{pseudo-absence datasets are considered individually, 
-##'     \emph{merging} algorithms and repetitions together}
-##'     \item{\code{algo} : }{algorithm datasets are considered individually, \emph{merging} 
-##'     pseudo-absence and repetitions together}
-##'     \item{\code{all} : }{all models are combined into one}
+##'     \item \code{PA+run} : each combination of pseudo-absence and repetition 
+##'     datasets is done, \emph{merging} algorithms together
+##'     \item \code{PA+algo} : each combination of pseudo-absence and algorithm datasets 
+##'     is done, \emph{merging} repetitions together
+##'     \item \code{PA} : pseudo-absence datasets are considered individually, 
+##'     \emph{merging} algorithms and repetitions together
+##'     \item \code{algo} : algorithm datasets are considered individually, \emph{merging} 
+##'     pseudo-absence and repetitions together
+##'     \item \code{all} : all models are combined into one
 ##'   }
 ##'   Hence, depending on the chosen method, the number of ensemble models built will vary. \cr
 ##'   \emph{Be aware that if no evaluation data was given to the 
@@ -145,7 +145,7 @@
 ##' 
 ##'   \item{Evaluation metrics}{
 ##'   \itemize{
-##'     \item{\bold{\code{metric.select}} : }{the selected metrics must be chosen among the ones used
+##'     \item \bold{\code{metric.select}} : the selected metrics must be chosen among the ones used
 ##'     within the \code{\link{BIOMOD_Modeling}} function to build the \code{model.output} object,
 ##'     unless \code{metric.select = 'user.defined'} and therefore values will be provided through
 ##'     the \code{metric.select.table} parameter. \cr In the case of the selection of several
@@ -157,50 +157,50 @@
 ##'       was given to argument \code{em.algo}
 ##'       \item weight models if \code{'EMwmean'} was given to argument \code{em.algo}
 ##'     }
-##'     }
-##'     \item{\bold{\code{metric.select.thresh}} : }{as many values as evaluation metrics
+##'     \item \bold{\code{metric.select.thresh}} : as many values as evaluation metrics
 ##'     selected with the \code{metric.select} parameter, and defining the corresponding quality
 ##'     thresholds below which the single models will be excluded from the ensemble model
-##'     building.}
-##'     \item{\bold{\code{metric.select.table}} : }{a \code{data.frame} must be given if
+##'     building.
+##'     \item \bold{\code{metric.select.table}} : a \code{data.frame} must be given if
 ##'     \code{metric.select = 'user.defined'} to allow the use of evaluation metrics other than
 ##'     those calculated within \pkg{biomod2}. The \code{data.frame} must contain as many columns
 ##'     as \code{models.chosen} with matching names, and as many rows as evaluation metrics to be
 ##'     used. The number of rows must match the length of the \code{metric.select.thresh}
 ##'     parameter. The values contained in the \code{data.frame} will be compared to those defined
 ##'     in \code{metric.select.thresh} to remove \emph{low quality} single models from
-##'     the ensemble model building.}
-##'     \item{\bold{\code{metric.select.dataset}} : }{a \code{character} determining the dataset
+##'     the ensemble model building.
+##'     \item \bold{\code{metric.select.dataset}} : a \code{character} determining the dataset
 ##'     which evaluation metric should be used to filter and/or weigh the
 ##'     ensemble models. Should be among \code{evaluation}, \code{validation} or
 ##'     \code{calibration}. By default \code{BIOMOD_EnsembleModeling} will use
 ##'     the validation dataset unless no validation is available in which case
-##'     calibration dataset are used.}
-##'     \item{\bold{\code{metric.eval}} : }{the selected metrics will be used to validate/evaluate
-##'     the ensemble models built}
+##'     calibration dataset are used.
+##'     \item \bold{\code{metric.eval}} : the selected metrics will be used to validate/evaluate
+##'     the ensemble models built
 ##'   }
 ##'   }
 ##' 
 ##'   \item{Ensemble-models algorithms}{The set of models to be calibrated on the data. \cr 
 ##'   6 modeling techniques are currently available :
 ##'   \itemize{
-##'     \item{\bold{\code{EMmean}} : }{Mean of probabilities over the selected models. Old name: \code{prob.mean}}
+##'     \item \bold{\code{EMmean}} : Mean of probabilities over the selected models. 
+##'     Old name: \code{prob.mean}
 ##'     
-##'     \item{\bold{\code{EMmedian}} : }{Median of probabilities over the selected models \cr 
+##'     \item \bold{\code{EMmedian}} : Median of probabilities over the selected models \cr 
 ##'     The median is less sensitive to outliers than the mean, however it requires more 
 ##'     computation time and memory as it loads all predictions (on the contrary to the mean or 
-##'     the weighted mean). Old name: \code{prob.median}}
+##'     the weighted mean). Old name: \code{prob.median}
 ##'     
-##'     \item{\bold{\code{EMcv}} : }{Coefficient of variation (sd / mean) of probabilities 
+##'     \item \bold{\code{EMcv}} : Coefficient of variation (sd / mean) of probabilities 
 ##'     over the selected models \cr 
 ##'     This model is not scaled. It will be evaluated like all other ensemble models although its 
 ##'     interpretation will be obviously different. CV is a measure of uncertainty rather a 
 ##'     measure of probability of occurrence. If the CV gets a high evaluation score, it means 
 ##'     that the uncertainty is high where the species is observed (which might not be a good 
 ##'     feature of the model). \emph{The lower is the score, the better are the models.} 
-##'     CV is a nice complement to the mean probability.  Old name: \code{prob.cv}}
+##'     CV is a nice complement to the mean probability.  Old name: \code{prob.cv}
 ##'     
-##'     \item{\bold{\code{EMci}} & \bold{\code{EMci.alpha}} : }{Confidence interval around 
+##'     \item \bold{\code{EMci}} & \bold{\code{EMci.alpha}} : Confidence interval around 
 ##'     the mean of probabilities of the selected models \cr 
 ##'     It is also a nice complement to the mean probability. It creates 2 ensemble models : 
 ##'     \itemize{
@@ -214,9 +214,8 @@
 ##'     \bar{x} +  \frac{t_\alpha sd }{ \sqrt{n} }]}
 ##'     \cr
 ##'     Old parameter name: \code{prob.ci} & \code{prob.ci.alpha}
-##'     }
 ##'     
-##'     \item{\bold{\code{EMca}} : }{Probabilities from the selected models are 
+##'     \item \bold{\code{EMca}} : Probabilities from the selected models are 
 ##'     first transformed into binary data according to the thresholds defined when building the 
 ##'     \code{model.output} object with the \code{BIOMOD_Modeling} function, maximizing the 
 ##'     evaluation metric score over the testing dataset. The committee averaging score is 
@@ -231,13 +230,13 @@
 ##'     of uncertainty. When the prediction is close to \code{0} or \code{1}, it means that all 
 ##'     models agree to predict \code{0} or \code{1} respectively. When the prediction is around 
 ##'     \code{0.5}, it means that half the models predict \code{1} and the other half \code{0}. 
-##'     \cr Old parameter name: \code{committee.averaging}}
+##'     \cr Old parameter name: \code{committee.averaging}
 ##'     
-##'     \item{\bold{\code{EMwmean}} & \bold{\code{EMwmean.decay}} : }{
+##'     \item \bold{\code{EMwmean}} & \bold{\code{EMwmean.decay}} : 
 ##'     Probabilities from the selected models are weighted according to their evaluation scores 
 ##'     obtained when building the \code{model.output} object with the \code{BIOMOD_Modeling} 
 ##'     function (\emph{better a model is, more importance it has in the ensemble}) and summed. \cr
-##'     Old parameter name: \code{prob.mean.weight} & \code{prob.mean.weight.decay}} 
+##'     Old parameter name: \code{prob.mean.weight} & \code{prob.mean.weight.decay}
 ##'   }
 ##'   
 ##' The \code{EMwmean.decay} is the ratio between a weight and the next or previous one. 

diff --git a/R/BIOMOD_FormatingData.R b/R/BIOMOD_FormatingData.R
@@ -99,8 +99,8 @@
 ##' 
 ##' A \code{\link{BIOMOD.formated.data}} object that can be used to build species distribution 
 ##' model(s) with the \code{\link{BIOMOD_Modeling}} function. \cr
-##' \code{\href{BIOMOD.formated.data.html}{print/show}}, \code{\href{plot.html}{plot}} and 
-##' \code{\href{summary.html}{summary}} functions are available to have a summary of the 
+##' \href{BIOMOD.formated.data.html}{\code{print/show}}, \href{plot.html}{\code{plot}} and 
+##' \href{summary.html}{\code{summary}} functions are available to have a summary of the 
 ##' created object. 
 ##' 
 ##' 
@@ -132,17 +132,15 @@
 ##' 
 ##' \bold{Concerning pseudo-absence selection (see \code{\link{bm_PseudoAbsences}}) :}
 ##' \itemize{
-##'   \item{if both presence and absence data are available, and there is enough absences :
+##'   \item if both presence and absence data are available, and there is enough absences :
 ##'   set \code{PA.nb.rep = 0} and no pseudo-absence will be selected.
-##'   }
-##'   \item{if no absence data is available, several pseudo-absence repetitions  
+##'   \item if no absence data is available, several pseudo-absence repetitions  
 ##'   are recommended (to estimate the effect of pseudo-absence selection), as well as high 
 ##'   number of pseudo-absence points. \cr
 ##'   \emph{Be sure not to select more pseudo-absence points than maximum number of pixels in 
 ##'   the studied area !}
-##'   }
-##'   \item{it is possible now to create several pseudo-absence repetitions with different 
-##'   number of points, BUT with the same sampling strategy. \cr \cr \cr \cr}
+##'   \item it is possible now to create several pseudo-absence repetitions with different 
+##'   number of points, BUT with the same sampling strategy. \cr \cr \cr \cr
 ##' }
 ##' 
 ##' \describe{

diff --git a/R/BIOMOD_Modeling.R b/R/BIOMOD_Modeling.R
@@ -109,7 +109,7 @@
 ##'   \item a \emph{hidden} folder, named \code{.BIOMOD_DATA}, and containing outputs related 
 ##'   files (original dataset, calibration lines, pseudo-absences selected, predictions, 
 ##'   variables importance, evaluation values...), that can be retrieved with 
-##'   \code{\href{https://biomodhub.github.io/biomod2/reference/getters.out.html}{get_[...]}} 
+##'   \href{https://biomodhub.github.io/biomod2/reference/getters.out.html}{\code{get_[...]}} 
 ##'   or \code{\link{load}} functions, and used by other \pkg{biomod2} functions, like 
 ##'   \code{\link{BIOMOD_Projection}} or \code{\link{BIOMOD_EnsembleModeling}}
 ##' }

diff --git a/R/BIOMOD_Projection.R b/R/BIOMOD_Projection.R
@@ -89,22 +89,22 @@
 ##' 
 ##' \code{...} can take the following values :
 ##' \itemize{
-##   \item{\code{clamping.level} : }{a \code{logical} value defining whether \code{clamping.mask} 
+##   \item \code{clamping.level} : a \code{logical} value defining whether \code{clamping.mask} 
 ##   cells with at least one variable out of its calibration range are to be removed from the 
 ##   projections or not
-##'   \item{\code{omit.na} : }{a \code{logical} value defining whether all not fully referenced 
-##'   environmental points will get \code{NA} as predictions or not}
-##'   \item{\code{on_0_1000} : }{a \code{logical} value defining whether \code{0 - 1} probabilities 
-##'   are to be converted to \code{0 - 1000} scale to save memory on backup}
-##'   \item{\code{do.stack} : }{a \code{logical} value defining whether all projections are to be 
+##'   \item \code{omit.na} : a \code{logical} value defining whether all not fully referenced 
+##'   environmental points will get \code{NA} as predictions or not
+##'   \item \code{on_0_1000} : a \code{logical} value defining whether \code{0 - 1} probabilities 
+##'   are to be converted to \code{0 - 1000} scale to save memory on backup
+##'   \item \code{do.stack} : a \code{logical} value defining whether all projections are to be 
 ##'   saved as one \code{\link[terra:rast]{SpatRaster}} object or several 
 ##'   \code{\link[terra:rast]{SpatRaster}} files (\emph{the default if projections are too heavy to 
-##'   be all loaded at once in memory})}
-##'   \item{\code{keep.in.memory} : }{a \code{logical} value defining whether all projections are 
-##'   to be kept loaded at once in memory, or only links pointing to hard drive are to be returned}
-##'   \item{\code{output.format} : }{a \code{character} value corresponding to the projections 
+##'   be all loaded at once in memory})
+##'   \item \code{keep.in.memory} : a \code{logical} value defining whether all projections are 
+##'   to be kept loaded at once in memory, or only links pointing to hard drive are to be returned
+##'   \item \code{output.format} : a \code{character} value corresponding to the projections 
 ##'   saving format on hard drive, must be either \code{.grd}, \code{.img}, \code{.tif} or \code{.RData} (the 
-##'   default if \code{new.env} is given as \code{matrix} or \code{data.frame})}
+##'   default if \code{new.env} is given as \code{matrix} or \code{data.frame})
 ##' }
 ##' 
 ##' 

diff --git a/R/BIOMOD_RangeSize.R b/R/BIOMOD_RangeSize.R
@@ -25,22 +25,22 @@
 ##'   \item{Compt.By.Species}{a \code{data.frame} containing the summary of range change for each 
 ##'   comparison
 ##'   \itemize{
-##'     \item{\code{Loss} : }{number of pixels predicted to be lost}
-##'     \item{\code{Stable0} : }{number of pixels not currently occupied and not predicted to be}
-##'     \item{\code{Stable1} : }{number of pixels currently occupied and predicted to remain 
-##'     occupied}
-##'     \item{\code{Gain} : }{number of pixels predicted to be gained}
-##'     \item{\code{PercLoss} : }{percentage of pixels currently occupied and predicted to be lost 
-##'     (\code{Loss / (Loss + Stable1)})}
-##'     \item{\code{PercGain} : }{percentage of pixels predicted to be gained compare to the 
-##'     number of pixels currently occupied (\code{Gain / (Loss + Stable1)})}
-##'     \item{\code{SpeciesRangeChange} : }{percentage of pixels predicted to change (loss or gain) 
-##'     compare to the number of pixels currently occupied (\code{PercGain - PercLoss})}
-##'     \item{\code{CurrentRangeSize} : }{number of pixels currently occupied}
-##'     \item{\code{FutureRangeSize0Disp} : }{number of pixels predicted to be occupied, assuming 
-##'     no migration}
-##'     \item{\code{FutureRangeSize1Disp} : }{number of pixels predicted to be occupied, assuming 
-##'     migration}
+##'     \item \code{Loss} : number of pixels predicted to be lost
+##'     \item \code{Stable0} : number of pixels not currently occupied and not predicted to be
+##'     \item \code{Stable1} : number of pixels currently occupied and predicted to remain 
+##'     occupied
+##'     \item \code{Gain} : number of pixels predicted to be gained
+##'     \item \code{PercLoss} : percentage of pixels currently occupied and predicted to be lost 
+##'     (\code{Loss / (Loss + Stable1)})
+##'     \item \code{PercGain} : percentage of pixels predicted to be gained compare to the 
+##'     number of pixels currently occupied (\code{Gain / (Loss + Stable1)})
+##'     \item \code{SpeciesRangeChange} : percentage of pixels predicted to change (loss or gain) 
+##'     compare to the number of pixels currently occupied (\code{PercGain - PercLoss})
+##'     \item \code{CurrentRangeSize} : number of pixels currently occupied
+##'     \item \code{FutureRangeSize0Disp} : number of pixels predicted to be occupied, assuming 
+##'     no migration
+##'     \item \code{FutureRangeSize1Disp} : number of pixels predicted to be occupied, assuming 
+##'     migration
 ##'   }
 ##'   }
 ##'   \item{Diff.By.Pixel}{an object in the same form than the input data (\code{proj.current} and