ggpmisc 0.4.4

Version 0.4.4 includes enhancements. An issue raised in GitHub and a question in StackOverflow asked for the possibility of changing how fitted lines are plotted based on the “goodness” of the fit. In addition an old question in StackOverflow highlighted the need of more intuitive support for annotations based on stats::cor.test(). In addition to implementing these enhancements we continued adding support for flipping of statistics controlled through formal parameter orientation as implemented in ‘ggplot2’ since version 3.3.0.

Changes compared to version 0.4.3, the previous version in CRAN are:

  • Add new function stat_correlation() to annotate plots with correlation estimates, their P-value, a test statistic and n computed with stats::cor.test(). In addition to formatted character strings, numeric values are included in the returned data frame to facilitate conditional display.
  • Update stat_poly_line() to optionally add columns n, p.value, r.squared , adj.r.squared and method to the returned data frame. Code breaking: This statistic no longer supports fitting of splines with methods such as loess . This could potentially break user code, in which case the solution is to use stat_smooth().
  • Update stat_ma_line() to optionally add columns n, p.value, r.squared and method to the returned data frame. (As only a slope can be fitted, adj.r.squared is irrelevant.)
  • Update stat_quant_line() and stat_quant_band() to optionally add n and method columns to the returned data frame. (No exact equivalent of r.squared exists for quantile regression.)
  • Update stat_fit_residuals() to optionally return weighted
  • Update stat_peaks() and stat_valleys() to allow flipping with new parameter orientation.

Documentation web site at includes all help pages, with output from all examples, vignettes as well as a changelog in HTML format.

NOTE: Version 0.4.4 is on its way to CRAN.

Please raise issues concerning bugs or enhancements to this package through GitHub

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