plotall: Visualise climate window data
In climwin: Climate Window Analysis

Description Usage Arguments Value Author(s) Examples

Creates a panel of plots to help visualise climate window data.

plotall(
  dataset,
  datasetrand = NULL,
  bestmodel = NULL,
  bestmodeldata = NULL,
  cw1 = 0.95,
  cw2 = 0.5,
  cw3 = 0.25,
  title = NULL,
  arrow = FALSE
)

`dataset`	A dataframe containing information on all fitted climate windows. Output from `slidingwin`.
`datasetrand`	A dataframe containing information on all fitted climate windows using randomised data. Output from `randwin`.
`bestmodel`	A model object. The strongest climate window model. Returned from `singlewin` or `slidingwin`.
`bestmodeldata`	A dataframe containing the biological and climate data used to fit the strongest climate window model. Output from `singlewin` or `slidingwin`.
`cw1, cw2, cw3`	Cumulative weight levels used to visualise model weight distribution. See `plotweights` for more detail.
`title`	Title of the plot panel.
`arrow`	TRUE or FALSE. Add arrows to plots to pinpoint best window.

Will return a panel of 6-8 plots:

DeltaAICc: A colour plot of model deltaAICc values (larger negative values indicate stronger models). DeltaAICc is the difference between AICc of each climate window model and the baseline model containing no climate data.
Model weight: A plot showing the distribution of cumulative model weights. Gradient levels determined by parameters cw1, cw2 and cw3. Darker areas have a higher chance of containing the best climate window. Also returns the percentage of models within the 95
Model betas: A colour plot of model beta estimates. Where applicable, 2nd order coefficients (quadratic) and 3rd order coefficients (cubic) will be plotted separately.
Histogram(s): If datasetrand is provided, plotall will return a histogram showing the deltaAICc of randomised data. This can help determine the likelihood of obtaining a deltaAICc value for a fitted climate window model at random. plotall will also use pvalue to return values of Pc and PdeltaAICc.
Boxplots: Two boxplots showing the start and end time for a subset of best climate windows. Best climate windows make up the cumulative model weight equivalent to the largest value of cw1, cw2 and cw3. Values above boxplots represent the median values.
Best Model: If bestmodel and bestmodeldata are provided, plotall will create a scatterplot to show the fit of the best model through the data.

Liam D. Bailey and Martijn van de Pol

# Visualise a fixed climate window generated for dataframes Mass and MassClimate

data(MassOutput)
data(Mass)
data(MassClimate)

single <- singlewin(xvar = list(Temp = MassClimate$Temp), 
                   cdate = MassClimate$Date, bdate = Mass$Date, 
                   baseline = lm(Mass ~ 1, data = Mass), 
                   range = c(72, 15), 
                   stat = "mean", func = "lin", 
                   type = "absolute", refday = c(20, 5), 
                   cmissing = FALSE, cinterval = "day")
           
plotall(dataset = MassOutput, bestmodel = single$BestModel, 
       bestmodeldata = single$BestModelData,
       cw1 = 0.95, cw2 = 0.5, cw3 = 0.25, title = "Mass")