R package 'ggpmisc'
Package 'ggpmisc' (Miscellaneous Extensions to 'ggplot2') is a set of extensions to R package 'ggplot2' (>= 2.1.0) which I hope will be useful when plotting diverse types of data. Currently available stats add the following statistics, geoms and function:
stat_peaks()find and label local or global maxima in y.
stat_valleys()find and label local or global minima in y.
stat_poly_eq()add a label for a fitted linear model to a plot, label can be the fitted polynomial equation, R^2, BIC, AIC.
stat_fit_deviations()display residuals from a model fit as segments linking observed and fitted values.
stat_fit_residuals()residuals from a model fit.
stat_fit_augment()data augmented with fitted values and statistics using package 'broom'.
stat_fit_glance()one-row summary data frame for a fitted linear model using package 'broom'.
stat_debug_panel()print data received as input by a stat's group and panel functions respectively. Useful for debugging new statistics and for exploring how ggplot works.
geom_debug()print data received as input by a geom.
try_data_frame()convert an R object into a data frame. Specially useful for plotting time series (using internally package '') which are returned with x data as POSIXct, allowing direct plotting with 'ggplot2' and packages extending 'ggplot2'.
Please, see the web site r4photobiology for details and update notices. Other packages, aimed at easing photobiology-related calculations including the quantification of biologically effective radiation in meteorology are available as part of a suite described at the same website.
The current release of 'ggpmisc' is available through CRAN for R (>= 3.2.0).