- 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 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 R
^{2}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.

- 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.

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.

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

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.

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.

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.

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.)

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).

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 \(R^2\) 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*Equations and other labels may render slightly differently than in previous versions as now`output.type`

is other than`"expression"`

.`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"`

.

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()`

.

- Update the documentation of
`geom_plot()`

. - Revise handling of rounding for \(R^2\) 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.

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

**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.

- Update
`stat_fit_tb()`

to support renaming of terms/parameter names in the table (Suggested by Big Old Dave and Z. Lin). In addition implement selection, reordering and renaming of columns and terms/parameters using positional indexes and pattern matching of truncated names in addition to whole names. Improve formatting of small*P*-values. - Update
`stat_fmt_tb()`

to support the same expanded syntax as`stat_fit_tb()`

. - Add
`stat_dens1d_filter()`

,`stat_dens1d_filter_g()`

and`stat_dens1d_labels()`

, to complement existing`stat_dens2d_filter()`

,`stat_dens2d_filter_g()`

and`stat_dens2d_labels()`

. - Update
`stat_dens2d_filter()`

,`stat_dens2d_filter_g()`

and`stat_dens2d_labels()`

adding formal parameters`keep.sparse`

and`invert.selection`

, as available in the new 1D versions. - Update
`stat_dens2d_labels()`

to accept not only character strings but also functions as argument to`label.fill`

as the new`stat_dens1d_labels()`

does. - Revise documentation including the
*User Guide*.

- Override
`ggplot2::annotate()`

adding support for aesthetics`npcx`

and`npcy`

. - Add
`stat_summary_xy()`

and`stat_centroid()`

. - Revise
`stat_poly_eq()`

to support labelling of equations according to group. - Implement
`output.type`

`"markdown"`

in`stat_poly_eq()`

usable with`geom_richtext()`

from package ‘ggtext’.

- Add support for “table themes” to geom_table() and
`geom_table_npc()`

.

- Add support for p.value.label and f.value.label to
`stat_poly_eq()`

. - Update to track deprecations in ‘ggplot2’ (>= 3.3.0).

- Fix bug in
`stat_poly_eq()`

. - Minor revision of the
*User Guide*and documentation.

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).

Add support for

*volcano*and*quadrant**plots*of outcomes.Add geometries

`geom_vhlines()`

and`geom_quadrant_lines()`

.Add convenience scales

`scale_x_logFC()`

and`scale_y_logFC()`

for data expressed as fold change.Add convenience scales

`scale_x_Pvalue()`

, scale_y_Pvalue(),`scale_x_FDR()`

,`scale_y_FDR()`

.Add convenience scales

`scale_colour_outcome()`

,`scale_fill_outcome()`

and`scale_shape_outcome()`

for data expressed as ternary or binary outcomes.Add conversion functions

`outcome2factor()`

and`threshold2factor()`

to convert vectors of numeric outcomes into factors with 2 or 3 levels.Add conversion function

`xy_outcomes2factor()`

and`xy_thresholds2factor()`

to combine two vectors of numeric outcomes into a 4-level factor.Improve support for model-fit annotations.

Update

`stat_poly_eq()`

so that optionally instead of text labels it can return numeric values extracted from the fit object.Document with examples how to pass weights and covariates to statistics based on methods from package ‘broom’. Highlight the differences among

`stat_poly_eq()`

and the`stat_fit_xxx()`

statistics implemented using package ‘broom’.Revise

`stat_apply_fun()`

to allow simultaneous application of functions to*x*and*y*aesthetics, and handling of`diff()`

and other functions returning slightly shorter vectors than their input.Support in

`stat_fit_tb()`

,`stat_fit_augment()`

,`stat_fit_tidy()`

and`stat_fit_glance()`

the use of character strings as position arguments for parameters`label.x`

and`label.y`

when using geoms based on*x*and*y*aesthetics in addition to when using those taking the`npcx`

and`npcy`

aesthetics.

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().

- Add
`geom_text_npc()`

and`geom_label_npc()`

using aesthetics npcx and npcy. - Add
`geom_table_npc()`

using aesthetics npcx and npcy. - Add
`geom_plot()`

and`geom_plot_npc()`

which can be used to add inset plots to a ggplot. - Add
`geom_grob()`

and`geom_grob_npc()`

which can be used to add inset*grobs*to a ggplot. - Add
`geom_x_margin_point()`

,`geom_y_margin_point()`

,`geom_x_margin_arrow()`

and`geom_y_margin_arrow()`

which behave similarly to`geom_hline()`

and`geom_vline()`

but plot points or arrows instead of lines. Add`geom_x_margin_grob()`

and`geom_y_margin_grob()`

with similar behaviour but for adding*grobs*. - Revise textual-summary statistics to use the new
*npc*version of geometries. - This may break old code that used
`geom_table()`

and depended on the old default of`inherit.aes=TRUE`

. - Add “summarize” statistics for groups and panels.
- Add
`stat_apply_panel()`

and`stat_apply_group()`

. - Add workaround to
`stat_fit_glance()`

and improve diagnosis of unsupported input. Replace bad example in the corresponding documentation (workaround for bug reported by Robert White). - Update documentation.
- Add and revise examples.
- Revise vignette.

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.

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

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

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.

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.

- Revise
`stat_fit_tidy()`

so that it returns*p*-values for parameters, in addition to estimates and their standard errors. - BUG FIX: Revise
`geom_debug()`

adding missing default arguments. - Add functions for manipulation of layers in ggplot objects:
`delete_layers()`

,`append_layers()`

,`move_layers()`

,`shift_layers()`

,`which_layers()`

,`extract_layers()`

,`num_layers()`

,`top_layer()`

and`bottom_layer()`

.

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.

Fix bug in `stat_poly_equation()`

`eq.x.rhs`

argument ignored when using expressions.

- 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()`

.

- 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.

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.

- 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.

- Add support for
*tikz*in`stat_poly_eq()`

. - Fix bug in
`stat_poly_eq()`

. - Fix bug in
`geom_debug()`

. - Fix bug in
`stat_fit_augment()`

.

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.

- 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.

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

.

- Remove one example to remove a package dependency.

- Improve handling of time zones in
`try_data_frame()`

. - Revise documentation and vignette.

`stat_poly_eq()`

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

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.

- Rename
`stat_debug()`

as`stat_debug_group()`

and add`stat_debug_panel()`

. - Add
`stat_peaks()`

and`stat_valleys()`

(these are simpler versions of`ggspectra::stat_peaks()`

and`ggspectra::stat_valleys()`

for use with any numerical data (rather than light spectra).

*First version.*

- Add
`stat_poly_eq()`

- Add
`stat_debug()`