S3 method for class 'multi'. plot.multi
creates plots
for objects of class multi, using the R base plotting framework. Plots
of all model fits, the multimodel SAR curve (with confidence intervals)
and a barplot of the information criterion weights of the different
models can be constructed.
# S3 method for multi plot( x, type = "multi", allCurves = TRUE, xlab = NULL, ylab = NULL, pch = 16, cex = 1.2, pcol = "dodgerblue2", ModTitle = NULL, TiAdj = 0, TiLine = 0.5, cex.main = 1.5, cex.lab = 1.3, cex.axis = 1, yRange = NULL, lwd = 2, lcol = "dodgerblue2", mmSep = FALSE, lwd.Sep = 6, col.Sep = "black", pLeg = TRUE, modNames = NULL, cex.names = 0.88, subset_weights = NULL, confInt = FALSE, ... )
x  An object of class 'multi'. 

type  The type of plot to be constructed: either 
allCurves  A logical argument for use with 
xlab  Title for the xaxis. Only for use with 
ylab  Title for the yaxis. 
pch  Plotting character (for points). Only for use with 
cex  A numerical vector giving the amount by which plotting symbols (points) should be scaled relative to the default. 
pcol  Colour of the points. Only for use with 
ModTitle  Plot title (default is 
TiAdj  Which way the plot title is justified. 
TiLine  Places the plot title this many lines outwards from the plot edge. 
cex.main  The amount by which the plot title should be scaled relative to the default. 
cex.lab  The amount by which the axis titles should be scaled relative to the default. 
cex.axis  The amount by which the axis labels should be scaled relative to the default. 
yRange  The range of the yaxis. Only for use with 
lwd  Line width. Only for use with 
lcol  Line colour. Only for use with 
mmSep  Logical argument of whether the multimodel curve should be
plotted as a separate line (default = FALSE) on top of the others, giving
the user more control over line width and colour. Only for use with

lwd.Sep  If 
col.Sep  If 
pLeg  Logical argument specifying whether or not the legend should be
plotted (when 
modNames  A vector of model names for the barplot of weights (when

cex.names  The amount by which the axis labels (model names) should be
scaled relative to the default. Only for use with 
subset_weights  Only create a barplot of the model weights for models
with a weight value above a given threshold ( 
confInt  A logical argument specifying whether confidence intervals
should be plotted around the multimodel curve. Can only be used if
confidence intervals have been generated in the 
…  Further graphical parameters (see

In some versions of R and R studio, when plotting all model fits on the same plot with a legend it is necessary to manually extend your plotting window (height and width; e.g. the 'Plots' window of R studio) before plotting to ensure the legend fits in the plot. Extending the plotting window after plotting sometimes just stretches the legend.
Occasionally a model fit will converge and pass the model fitting checks
(e.g. residual normality) but the resulting fit is nonsensical (e.g. a
horizontal line with intercept at zero). Thus, it can be useful to plot
the resultant 'multi' object to check the individual model fits. To
rerun the sar_average
function without a particular model, simply
remove it from the obj
argument.
For visual interpretation of the model weights barplot it is necessary
to abbreviate the model names when plotting the weights of several
models. To plot fewer bars, use the subset_weights
argument to
filter out models with lower weights than a threshold value. To provide
a different set of names use the modNames
argument. The model
abbreviations used as the default are:
Pow = Power
PowR = PowerR
E1 = Extended_Power_model_1
E2 = Extended_Power_model_2
P1 = Persistence_function_1
P2 = Persistence_function_2
Loga = Logarithmic
Kob = Kobayashi
MMF = MMF
Mon = Monod
NegE = Negative_exponential
CR = Chapman_Richards
CW3 = Cumulative_Weibull_3_par.
AR = Asymptotic_regression
RF = Rational_function
Gom = Gompertz
CW4 = Cumulative_Weibull_4_par.
BP = BetaP_cumulative
Hel = Heleg(Logistic)
Lin = Linear_model
data(galap) #plot a multimodel SAR curve with all model fits included fit < sar_average(data = galap)#> #> Now attempting to fit the 20 SAR models: #> #>  multi_sars  multimodel SAR  #> > power : v #> > powerR : v #> > epm1 : v #> > epm2 : v #> > p1 : v #> > p2 : v #> > loga : v #> > koba : v #> > mmf : v #> > monod : v #> > negexpo : v #> > chapman : Warning: could not compute parameters statistics #> > weibull3 : v #> > asymp : v #> > ratio : v #> > gompertz : v #> > weibull4 : v #> > betap : v #> > heleg : v #> > linear : v #> #> Model fitting completed  all models succesfully fitted. Now undertaking model validation checks. #> Additional models will be excluded if necessary:#> #>#>#> 16 remaining models used to construct the multi SAR: #> Power, PowerR, Extended Power model 2, Persistence function 1, Persistence function 2, Logarithmic, Kobayashi, MMF, Monod, Negative exponential, Chapman Richards, Cumulative Weibull 3 par., Rational function, Gompertz, BetaP cumulative, Heleg(Logistic) #> plot(fit)#plot all model fits and the multimodel curve on top as a thicker line plot(fit, allCurves = TRUE, mmSep = TRUE, lwd.Sep = 6, col.Sep = "orange")