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Changelog

Source: NEWS.md

ggpmisc 0.5.6

  • Rename parameter trans of scale_y_Pvalue() into transform to track deprecation in ‘ggplot2’ 3.5.0.
  • Revise stat_multcomp() to flexibly include in labels, both when using “bars” and “letters”, the abbreviated name of the method used to adjust P-values (suggested by markbneal, Mark Neal).
  • Revise stat_multcomp() to flexibly include only when using “letters” an additional label with the critical P-value and the method used to adjust the empirical P-values (suggested by markbneal, Mark Neal).
  • Revise stat_multcomp() to support arbitrary sets of pairwise contrasts.
  • Rename parameters of stat_multcomp(): adjusted.type to p.adjust.method, and constrast.type to contrasts.
  • Change defaults used for p.adjust.method so that they depend on the argument passed to contrasts.
  • Accept in stat_correlation(), stat_poly_eq(), stat_ma_eq(), and stat_multcomp(), p.digits = Inf as a request to use scientific notation for p.value.label (suggested by wbvguo, Wenbin Guo).
  • Fix bug in stat_multcomp(): wrongly encoded letters in Tukey contrasts in case of grouping factors with more than nine levels.
  • Fix bug in stat_multcomp(): off-plot letter labels with Tukey contrasts in some plots with more than five groups.

ggpmisc 0.5.5

CRAN release: 2023-11-15

  • Fix decoding of orientation from formula to allow function calls on the rhs of formulas, e.g., I(y - 10) ~ x or I(x - 10) ~ y.
  • Export function find_peaks() which was previously internal.
  • Move transcriptomics example data objects to package ‘ggpp’.
  • Fix scrambled table in the vignette (reported by markbneal, Mark Neal).

ggpmisc 0.5.4

  • Add stat_multcomp() that computes adjusted p-values and constructs labels to annotate plots with results from multiple comparisons based on “Tukey” or “Dunnet” contrasts.
  • Fix bug affecting position of labels, e.g., when observations are not plotted: use scale range instead of data range.
  • Confidence intervals for r in stat_correlation() are no longer computed by default for methods other than Pearson, as when using bootstrap the computation can be time-consuming and occasionally fail. Previous default can be restored by passing 0.95 as argument to r.conf.level.

ggpmisc 0.5.3

CRAN release: 2023-06-24

  • Fix bug in stat_ma_line(): error triggered when returned values from computation of confidence band are missing. (Reported by rakelrpf as issue #36.)
  • Fix bug in stat_quant_eq(): rho.label showed the numeric value of AIC instead of rho.
  • Fix incompatibility of stat_poly_eq() (and other statistics) with package ‘gganimate’ (Bug reported by EvoLandEco as issue #38).
  • Improve handling of singular fits in model fitting in stat_poly_eq(), stat_ma_eq() and stat_quant_eq() (Use case from EvoLandEco in issue #38.).
  • Add parameter n.min to all statistics that fit a model or compute correlations. Default value is the previously hard-coded value, except in one case where the previously hard-coded value was wrong.
  • Add stat_fit_fitted().

ggpmisc 0.5.2

CRAN release: 2022-12-17

ggpmisc 0.5.1

CRAN release: 2022-10-15

  • Revise approach used to extract the formula from the fitted model object. Use formula() method on fitted model but fall-back onto the ‘formula’ argument in case of error or return NA if everything fails, without triggering an error condition.
  • Always include variables fm.tb.type, fm.class, fm.method, fm.formula, and fm.formula.chr in the data returned by stat_fit_tb(), and rename mf_tb into fm.tb for naming consistency.
  • Always include variable fm.formula in the data returned by all other textual-annotation statistics based on model fitting.
  • Include variables fm.class, fm.method, and fm.formula.chr in addition to fm.formula in the data returned by line plotting statistics based on model fitting when passed argument fm.values = TRUE.
  • Add scale_colour_logFC(), scale_color_logFC() and scale_fill_logFC().
  • Revise scale_colour_outcome() and scale_fill_outcome() adding flexibility to the value names and allowing a work-around for non-functional drop in manual scales due to a bug present in ‘ggplot2’ (only in versions 3.3.4, 3.3.5, 3.3.6).
  • Revise User Guide.
  • Update for compatibility with upcoming ‘ggplot2’ 3.4.0 (tested with v3.4.0-rc).

ggpmisc 0.5.0

CRAN release: 2022-08-12

  • Differently to the use in the R literature mf has been used in this package, instead of fm, to signify fitted model. This has changed in this version as formal parameter mf.values has been renamed fm.values and variable mf_tb in values returned by statistics renamed fm.value. Although these are code breaking changes, they are likely to cause difficulties only in isolated cases as defaults rarely need to be overridden.
  • Add function use_label() that greatly simplifies assembling and mapping combined labels from the values returned by stat_poly_eq(), stat_ma_eq(), stat_quant_eq() and stat_correlation().
  • Add variables fm.tb.type, fm.class, fm.method, and fm.formula.chr to the data returned by stat_fit_tb(), and rename mf_tb into fm.tb for naming consistency.
  • Add variables fm.class, fm.method, and fm.formula.chr to the data returned by all other textual-annotation statistics statistics based on model fitting.
  • Add confidence intervals for R (Pearson’s OLS correlation), τ (Kendall’s rank correlation) and ρ (Spearman’s rank correlation) to the values and labels returned by stat_correlation(). In the case of method = "pearson" assuming Normal distribution or estimated by bootstrap. For method = "kendall" and method = "spearman" only bootstrap estimates. These are implemented using package ‘confintr’.
  • Add confidence interval for R2 to the values and labels returned by stat_poly_eq() (implemented using package ‘confintr’).
  • Add θ (theta) to the values and labels returned by stat_ma_eq().
  • Add method.label to the data returned by stat_correlation(), stat_poly_eq(), stat_ma_eq() and stat_quant_eq().
  • Add experimental functions keep_tidy(), keep_glance() and keep_augment() as wrappers on methods tidy(), glance() and augment() from package ‘broom’. These new functions make it possible to keep a trace of the origin of the “broom-tidied” outputs.
  • Update documentation and User Guide.

ggpmisc 0.4.7

CRAN release: 2022-06-15

  • Fix bug in the handling of the weight aesthetic in stat_poly_eq(), stat_poly_line(), stat_quant_eq() and stat_quant_line().
  • The model formula is in calls to stat_poly_eq() and stat_quant_eq() now retrieved from the returned fitted model object before constructing the equation label. This makes it possible model selection within the function passed as argument to method. (Inspired by an answer read in Stackoverflow.)
  • Statistics now search for a matching function when an arbitrary name is supplied as a character string argument to parameter method.
  • The character string passed as argument to parameter method is now parsed so that it can contain both the name of a model fit function and the argument to be passed to this function’s own method parameter. (Backward compatibility is maintained.)
  • The stats that create equation labels now include a variable method in the returned data containing a character string with the method used in the model fit.

ggpmisc 0.4.6

CRAN release: 2022-04-10

This update fixes a significant bug. Although the problem, when triggered, is obvious by looking at the plot, please, update.

  • Fix bug in stat_peaks() and stat_valleys(). They could return wrong values for peaks and valleys if the rows in data in the ggplot object were not sorted by the value of x for all arguments to span different from null.

ggpmisc 0.4.5

CRAN release: 2021-12-11

This is a minor update for compatibility with ‘ggpp’ (>= 0.4.3) and fixing a wrong version number for ‘gginnards’ in DESCRIPTION.

ggpmisc 0.4.4

CRAN release: 2021-10-31

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(). We implemented these requested enhancements and continued adding support for flipping of statistics through parameter orientation as implemented in ‘ggplot2’ since version 3.3.0.

  • Update stat_poly_line() to optionally add columns n, p.value, r.squared , adj.r.squared and method to the returned data frame. 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 residuals.

  • Update stat_peaks() and stat_valleys() to allow flipping with new parameter orientation.

  • New function stat_correlation() to annotate plots with correlation estimates, their P-value, a test statistic and n computed with stats::cor.test(). Numeric values are included in the returned data frame to facilitate conditional display.

ggpmisc 0.4.3

CRAN release: 2021-09-03

Add statistics stat_ma_line() and stat_ma_eq() implementing model II regression based on package ‘lmodel2’ (major axis, standard major axis, and ranged major axis regression). Methods coef(), confint() and predict() for fit objects returned by lmodel2::lmodel2() are also implemented and exported.

Removed setting of fill to light blue in stat_quant_band() as there is no safe way of overriding the geom’s default.

ggpmisc 0.4.2-2

Fix major bug in stat_poly_eq() and stat_quant_eq() affecting only some R builds, reported and reproduced for Linux. (Reported by Flavio Lozano-Isla, T. BruceLee and Lewis Hooper, debugged with the help of Mark B. Neal.) Reported to affect versions 0.4.0, 0.4.1, 0.4.2 and 0.4.2-1.

ggpmisc 0.4.2-1

CRAN release: 2021-08-15

Fix a bug remaining in 0.4.2, that could result in after_stat() not being found. (Reported by Prof. Brian Ripley and Michael Steinbaugh.)

ggpmisc 0.4.2

CRAN release: 2021-08-04

Changes to Depends, Imports and Suggests, to solve errors and/or to avoid dependencies that are not needed. As a consequence package ‘broom’ is no longer automatically installed as a dependency of ‘ggpmisc’ and if used, will need to be explicitly installed by the user. Several examples are now run only if the necessary packages have been installed (Prof. Brian Ripley, Uwe Ligges and members of the CRAN’s team are thanked for package quality control).

ggpmisc 0.4.1

CRAN release: 2021-08-02

The suggestion from Mark Neal of adding support for quantile regression partly addressed in ggpmisc 0.4.0 has lead to additional enhancements in this version. The idea of supporting confidence bands for quantile regression came from Samer Mouksassi who also provided code examples. Additional suggestions from Mark Neal, Carl and other users have lead to bug fixes as well as to an interface with better defaults for arguments (see issue #1). Some other enhancements are based on my own needs or ideas.

  • Add support for robust regression using rlm and for fit function objects in stat_poly_eq().
  • Make it easier to use stat_poly_eq() and stat_quant_eq() with formula = x ~ y and other models in which the explanatory variable is y in addition to models with x as explanatory variable (this was already supported but the defaults for eq.with.lhs and eq.x.rhs were hard coded needing manual override while they are now set dynamically depending on the formula).
  • Revise stat_poly_eq() and stat_quant_eq() so that they pass to the geom by default a suitable value as argument to parse depending on output.type (enhancement suggested by Mark Neal in issue #11) and so that the default output.type is "markdown" if the argument passed to geom is one of "richtext" or "textbox", improving compatibility with package ‘ggtext’.
  • Revise stat_poly_eq() and stat_quant_eq() so that when output.type = "numeric" they return the coefficient estimates as numeric columns in data (problem with coefs.ls column in data when using facets reported by cgnolte in issue #12).
  • Revise stat_poly_eq() adding support for optional use of lower case r and p for R2 and P-value, respectively.
  • Fix bug in stat_poly_eq() and stat_quant_eq() resulting in mishandling of formulas using the + 0 notation to exclude the intercept (reported by orgadish in issue #10).
  • Add stat_poly_line(), which is a new interface to ggplot2::stat_smooth() accepting formula = x ~ y and other models in which the explanatory variable is y rather than x or setting orientation = "y". In contrast to ggplot2::stat_smooth(), stat_poly_line() has "lm" as default for method irrespective of the number of observations.
  • Add stat_quant_line() which is a merge of ggplot2::stat_smooth() and ggplot2::stat_quantile() accepting formula = x ~ y and other models in which the explanatory variable is y rather than x or setting orientation = "y" to fit models with x as explanatory variable. This statistic makes it possible to add to a plot a double quantile regression. stat_quant_line() supports plotting of confidence bands for quantile regression using ggplot2::geom_smooth() to create the plot layer.
  • Add stat_quant_band() which plots quantile regressions for three quantiles as a band plus a line, accepting formula = x ~ y and other models in which the explanatory variable is y rather than x or setting orientation = "y" to fit models with x as explanatory variable. By default the band uses "steelblue" as fill, to distinguish them from confidence bands.
  • Add support for quantile regression rq, robust regression rlm, and resistant regression lqs and function objects to stat_fit_residuals() and stat_fit_deviations() .
  • Make it possible to use stat_fit_residuals() and stat_fit_deviations() with formula = x ~ y and other models in which the explanatory variable is y in addition to models with x as explanatory variable.
  • Add weights to returned values by stat_fit_residuals() and stat_fit_deviations() and add support for the weight aesthetic as their input for parameter weights of the model fit functions.
  • Revise stat_poly_eq() and stat_quant_eq() so that by default they keep trailing zeros according to the numbers of significant digits given by coef.digits. A new parameter coef.keep.zeros can be set to FALSE to restore the deletion of trailing zeros. Be aware that even if the character label for the equation contains trailing zeros, if it is parsed into R an expression (as it is by default) the trailing zeros will be dropped at this later stage. Trailing zeros in the equation will be rendered to the plot only if output.type is other than "expression". Equations and other labels may render slightly differently than in previous versions as now sprintf() is used to format all labels.
  • Fix bug in stat_poly_eq() and stat_quant_eq() that resulted in bad/non-syntactical character strings for eq.label when output.type was different from its default of "expression".

ggpmisc 0.4.0

CRAN release: 2021-06-03

Package ‘ggpmisc’ has been split into two packages: ‘ggpp’ containing extensions to the grammar of graphics and ‘ggpmisc’ containing extensions related to plot decorations based on model fits, statistical summaries and other descriptors of the data being plotted. Package ‘ggpmisc’ depends on ‘ggpp’ with no visible changes for users. Package ‘ggpp’ can be loaded instead of ‘ggpmisc’ when only the extensions it contains are needed. Package ‘gginnards’ containing tools for editing ggplot objects as well as tools for inspecting them is an earlier spin-off from ‘gpmisc’.

The changes in this version stem for users’ questions and suggestions. Many thanks!

  • Add stat_quant_eq() based on quantile regression as implemented in package ‘quantreg’. (enhancement suggested by Mark Neal)

  • Add n.label and n to the values returned by stat_poly_eq()and stat_quant_eq(). (enhancement suggested by a question from ganidat)

  • Add r.squared, adj.r.squared, p.value and n as numeric values returned in addition to the corresponding character labels when stat_poly_eq() is called with output.type other than numeric. Similarly for n and rho in the case of stat_quant_eq(). (enhancement suggested by a question from Tiptop)

  • Fix bug in stat_poly_eq() leading to empty returned value when data contains too few observations to fit the model. (reported by ganidat)

  • Add support for quantile regression rq, robust regression rlm, and resistant regression lqs and function objects to stat_fit_deviations().

ggpmisc 0.3.9

CRAN release: 2021-04-04

  • Update the documentation of geom_plot().
  • Revise handling of rounding for R2 and P-value in stat_poly_eq().
  • Fix bug in stat_poly_eq() that resulted in no labels being displayed for any group when one group has too few distinct x-values to fit the polynomial (reported by user 5432156 “ganidat” in StackOverflow).
  • [Under development!] Link repositioned text to its original position with a segment or arrow: geom_linked_text(). Except for the drawing of segments or arrows this new geometry behaves as ggplot2::geom_text() . Note: Segments and arrows are drawn only if the position function used returns both the repositioned and original coordinates.
  • Add support for advanced nudging: position_nudge_centre() and position_nudge_line() compute the direction of nudging and return both the nudged and original positions.
  • Add support for simple nudging: position_nudge_to() nudges to new user-supplied position(s); position_nudge_keep() nudges to position(s) based on user-supplied position shift. These functions return both nudged and original position(s), which makes possible to draw connecting segments from text labels to the original position.

ggpmisc 0.3.8-1

CRAN release: 2021-01-27

  • Fix bug: suggested package not loaded in vignette Model-Based Plot Annotations resulting in “method not found” warning in some examples.

ggpmisc 0.3.8

CRAN release: 2021-01-25

  • CODE BREAKING: functions stat_fit_glance() , stat_fit_augment() , stat_fit_tidy() and stat_fit_tb() now import the tidiers from package ‘generics’ instead of from ‘broom’. As a result, users must now explicitly load the package where the methods to be used are defined, such as ‘broom’ or ‘broom.mixed’ or define them before calling these statistics.
  • Add formal parameter glance.args to stat_fit_glance() , parameter tidy.ars to stat_fit_tidy() and stat_fit_tb() and parameter augment.args to stat_fit_augment() as some specializations of broom::glance(), broom::tidy() and stat_fit_augment() accept arguments specific to a given fitting method.
  • Fix bug: stat_fit_tidy() would fail with quantreg::rq() and any other fit methods that do not return by default standard error estimates for parameter estimates (Thanks to Mark Neal for reporting the problem).
  • Revise stat_fit_glance(), stat_fit_augment() and stat_fit_tidy() to ensure compatibility with cor.test() and other functions that require an object rather than a quoted expression as argument for data .
  • Add formal parameter p.digits to stat_fit_tb().
  • New vignette explaining how the grammar of graphics has been expanded to better support annotations.
  • Fix bug: try_tibble.ts() and try_data_frame() did not handle correctly the conversion of dates for some time series, which also could affect ggplot.ts().
  • Fix bug: stat_peaks() and stat_valleys() generated wrong labels if a Date object was mapped to x (the bug did not affect POSIX or datetime, and was obvious as it resulted in a shift in dates by several decades).
  • Move git repository from Bitbucket to Github. Numbering of issues restarts from #1, but all old commits were transferred as is.
  • Set up Github action for CRAN-checks on Windows, OS X and Ubuntu.

ggpmisc 0.3.7

CRAN release: 2020-11-09

ggpmisc 0.3.6

CRAN release: 2020-09-07

ggpmisc 0.3.5

CRAN release: 2020-06-01

ggpmisc 0.3.4

CRAN release: 2020-04-22

  • Add support for p.value.label and f.value.label to stat_poly_eq().
  • Update to track deprecations in ‘ggplot2’ (>= 3.3.0).

ggpmisc 0.3.3

CRAN release: 2019-12-01

  • Fix bug in stat_poly_eq().
  • Minor revision of the User Guide and documentation.

ggpmisc 0.3.2

CRAN release: 2019-11-11

This version implements some new features and fixes bugs in the features introduced in version 0.3.1, please do rise an issue if you notice any remaining bugs! Some reported weaknesses in the documentation have been addressed. This updated version depends on ‘ggplot2’ (>= 3.2.1).

ggpmisc 0.3.1

CRAN release: 2019-04-02

This is a major update, with a few cases in which old code may need to be revised to work, and many cases in which there will be subtle differences in the positions of labels used as annotations. The many new features may still have some bugs, please do rise an issue if you notice one!

Version requiring ‘ggplot2’ (>= 3.1.0).

Add new geometries, several of them accepting x and y in npc units through the new aesthetics npcx and npcy, allowing positioning relative to plotting area irrespective of native data units and scale limits. These geometries are useful on their own for annotations in particular they allow consistent positioning of textual summaries. By default they do not inherit the plot’s aesthetic mappings making their behaviour remain by default in-between that of true geometries and that of annotate().

ggpmisc 0.3.0

CRAN release: 2018-07-16

Version requiring ‘ggplot2’ (>= 3.0.0), now in CRAN. Low level manipulation and debug methods and functions moved to new package ‘gginnards’ available through CRAN.

  • Remove debug stats and geoms -> ‘gginnards’.
  • Remove layer manipulation functions -> ‘gginnards’.
  • Add support for “weight” aesthetic in stat_poly_eq() (fixing bug reported by S.Al-Khalidi).
  • Add support for column selection and renaming to stat_fit_tb().
  • Add new statistic stat_fmt_tb() for formatting of tibbles for addition to plots as tables.
  • Rename stat_quadrat_count() into stat_quadrant_count() (miss-spelling).
  • Revise vignette.

ggpmisc 0.2.17.9902

Non-CRAN version with additional functionality, but requiring the development version of ‘ggplot2’.

  • Track code breaking change in ‘ggplot2’ commit #2620 (2018-05-17).

ggpmisc 0.2.17.9900

Non-CRAN version with additional functionality, but requiring the development version of ‘ggplot2’ >= 2.2.1.9000 (>= commit of 2017-02-09) from Github. Visit

  • geom_table(), a geom for adding a layer containing one or more tables to a plot panel.
  • stat_fit_tb() a stat that computes a tidy tabular version of the summary or ANOVA table from a model fit.

ggpmisc 0.2.17

CRAN release: 2018-05-04

CRAN version

  • Add stat_quadrat_count() a stat that computes the number of observations in each quadrant of a plot panel ignoring grouping.

  • Fix bugs, one of which is code breaking: the names of returned parameter estimates have changed in stat_fit_tidy() now pasting "_estimate" to avoid name clashes with mapped variables.

ggpmisc 0.2.16

CRAN release: 2017-09-17

ggpmisc 0.2.15

CRAN release: 2017-05-14

Add stat_fit_tidy() implemented using broom::tidy(). Makes it possible to add the fitted equation for any fitted model supported by package ‘broom’, as long as the user supplies within aes() the code to build a label string. Update user guide.

ggpmisc 0.2.14

CRAN release: 2017-02-02

Fix bug in stat_poly_equation() eq.x.rhs argument ignored when using expressions.

ggpmisc 0.2.13

CRAN release: 2016-11-26

  • Fix bugs in try_tibble() and try_data_frame() which made them fail silently with some objects of class "ts" in the case of numeric (decimal date) index for time. In addition lack of special handling for classes "yearmon" and "yearqrt" from package ‘zoo’, lead to erroneous date shifts by a few days.
  • Add methods ggplot.ts() and ggplot.xts().

ggpmisc 0.2.12

CRAN release: 2016-10-22

  • Change default value for parameter label.fill in stat_dens2d_labels() from NA to "".
  • Improve documentation using current ‘ggrepel’ version, which implements changes that make stat_dens2d_labels() useful.

ggpmisc 0.2.11

  • Add stat_dens2d_labels(), a statistic that resets label values to NA by default, or any character string supplied as argument, in regions of a panel with high density of observations.

  • Add stat_den2d_filter(), a statistic that filters-out/filters-in observations in regions of a panel with high density of observations. These two statistics are useful for labeling or highlighting observations in regions of a panel with low density. Both stats use a compute_panel function.

  • Add stat_den2d_filter_g(), a statistic that filters-out/filters-in observations in regions of a group with high density of observations. This statistics is useful for highlighting observations. It uses a compute_group function. They use internally MASS:kde2d to estimate densities and default values for parameters are adjusted dynamically based on the number of observations.

ggpmisc 0.2.10

CRAN release: 2016-07-30

  • Add user-requested feature: allow user to specify number ‘digits’ used in formatting numbers in labels in stat_poly_eq().
  • Update try_data_frame() to return an object of class "tibble" and add try_tibble() as synonym.
  • Update documentation and start using package ‘staticdocs’ to build a documentation web site.

ggpmisc 0.2.9

CRAN release: 2016-06-18

ggpmisc 0.2.8

CRAN release: 2016-05-22

  • Enhance stat_poly_eq() so that 1) position of labels according to npc (relative positions using normalized coordinates), as well as by named positions "top", "bottom", "right", "left" and "center" is now implemented; 2) when grouping is present, suitable vjust values are computed to automatically position the labels for the different groups without overlap. Default label positions are now relative to the range of each panel’s x and y scales, eliminating in most cases the need to manually tweak label positions.

  • Add stat_fit_glance() uses package ‘broom’ for maximum flexibility in model function choice when wanting to add labels based on information from a model fit, at the expense of very frequently having to explicitly set aesthetics, and always having to add code to do the formatting of the values to be used in labels. Label position is as described above for stat_poly_eq().

  • Add stat_fit_deviations() for highlighting residuals in plots of fitted models. This statistic currently supports only lm() fits. By default geom “segment” is used to highlight the deviations of the observations from a fitted model.

  • Add stat_fit_residuals() for plotting residuals from a fitted model on their own in plots matching plots of lm fits plotted with stat_smooth() even with grouping or facets. This statistic currently supports only lm() fits. By default geom “point” is used to plot the residual from a fitted model.

  • Add preliminary version of stat_fit_augment(), which uses package ‘broom’ for maximum flexibility in model function choice, to augment the data with additional columns of values derived from a model fit.

ggpmisc 0.2.7

CRAN release: 2016-03-22

  • Add support for AIC and BIC labels to stat_poly_eq().
  • Add pretty-printing of parameter values expressed in engineering notation in stat_poly_eq().
  • Add support for user-supplied label coordinates in stat_poly_eq().
  • Improve stat_debug_panel() and stat_debug_group() so that they can optionally print to the console a summary of the data received as input.
  • Add geom_debug(), a geom that summarizes its data input to the console, and produces no visible graphical output.

ggpmisc 0.2.6

CRAN release: 2016-02-25

  • Add support for user-supplied lhs and for user-supplied rhs-variable name in the equation label in stat_poly_eq().

ggpmisc 0.2.5

CRAN release: 2016-01-30

  • Remove one example to remove a package dependency.

ggpmisc 0.2.4

  • Improve handling of time zones in try_data_frame().
  • Revise documentation and vignette.

ggpmisc 0.2.3

  • stat_poly_eq() changed to include the lhs (left hand side) of the equation by default.

ggpmisc 0.2.2

  • Add function try_data_frame() to convert R objects including time series objects of all classes accepted by try.xts() into data frames suitable for plotting with ggplot().

  • Update stat_peaks() and stat_valleys() to work correctly when the x aesthetic uses a Date or Datetime continuous scale such as ggplot() sets automatically for POSIXct variables mapped to the x aesthetic.

ggpmisc 0.2.1

ggpmisc 0.1.0

First version.