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# ggpmisc 0.7.0

The main changes in this version improve and expand the generation of labels,
adding support for `geom_latex()` from package 'xdvir' and for `geom_marquee()`
from package 'marquee', and enhance the maths rendering in labels generated
with Markdown markup. Use of plotmath expressions remains the default for
geoms from 'ggpp' and from 'ggplot2'.

-   Automatic selection of `output.type = "latex.eqn"` when `"latex"` is passed
as argument to parameter `geom` of statistics that generate labels, including
fitted model equations.
-   With new `output.type == "latex.eqn"` and `output.type == "latex.deqn"` 
labels are fenced with `$` or `$$` to be readily formatted as $\LaTeX$ 
in math mode. As earlier `output.type == "latex"` outputs the same labels without
the fences in case they are to be combined into a complex math mode equation.
-   Bugs in the $\LaTeX$ encodings of a couple of labels have been fixed.
-   Automatic selection of `output.type = "marquee"` when `"marquee"` is passed
as argument to parameter `geom` of statistics that generate labels, including
fitted model equations.
-   With new `output.type == "marquee"` sub- and superscripts are encoded using
the span definitions used be 'marquee' instead of the embedded HTML used with
`output.type == "mardown"`.
-   With both `output.type == "markdown"` and `output.type == "marquee"`, use
formatting that results in typeset equations that better match those encoded as
plotmath expressions.
-   Track changes in 'gginnards' (>= 0.2.0) in examples and docs.
-   In all model fitting _stats_ add support for method `"lts"` passed as a
character string for a trimmed regression fitted with `robustbase::ltsReg()`.
-   Breaking: In all model fitting _stats_ remove support for method `"lqs"`
passed as a character string, as `lts` is preferred.
-   Support `smatr::ma()` and `smatr::sma()` in `stat_fit_residuals()`.
-   Non-standard packages hosting model fit functions recognized by their names
passed as character strings are now installed only when the methods are used for
the first time.
-   A new on-line-only article gives examples of the use of 'ggpmisc' together
with R package 'xdvir' and another one compares plot annotations created with
the different output types and matching geometries.
-   Update documentation for all statistics to include an automatically 
generated _Aesthetics_ section.
-   Model fitting, extraction of fitted and other values, argument-decoding and
label formatting and label assembly code refactored to avoid duplication and 
ensure consistency.
-   Bug in the handling of `orientation` fixed.

**Note:** When 'ggpmisc' >= 0.7.0 is used together with 'ggpp' >= 0.6.0 and 
'ggplot2' >= 4.0.0 the geom element of 'ggplot2' themes is obeyed.

# ggpmisc 0.6.3

This version adds support for additional model fitting approaches
and packages. It also implements an optional call to `set.seed()` immediately
ahead of calling model fit functions.

_Parameter `orientation` is not yet supported in all statistics._

-   Add `stat_distrmix_line()` and `stat_distrmix_eq()` currently supporting 
    only Normal mixture models fitted with `mixtools::normalmixEM()`.
-   Support `log()` and `sqrt()` transformations for `local.reference` in
    `find_peaks()`, `find_valleys()`, `stat_peaks()` and `stat_valleys()`.
-   Support `smatr::ma()` and `smatr::sma()` in `stat_poly_eq()` and in
    `stat_poly_line()`. (Confidence band is only for slope.)
-   Support `segmented::segmented()` and `segmented::segreg()` in 
    `stat_poly_eq()`, `stat_poly_line()`, `stat_fit_fitted()`, 
    `stat_fit_residuals()` and `stat_fit_deviations()`.
-   Support `lspline::lspline()` in `stat_poly_eq()`, `stat_poly_line()`,
    `stat_fit_fitted()`, `stat_fit_residuals()` and `stat_fit_deviations()`.
-   `stat_poly_eq()` return for all `output.type`s several fitted numerical 
    values that previously were only returned for `output.type = "numeric"`.
-   Add parameter `fit.seed` to all model-fitting statistics as supported model
    fit methods include some that depend on the random number generator (RNG).
-   Add parameter `fit.seed` to `stat_correlation()` as some supported CI
    computations depend on the RNG.
-   Rewrite `stat_quant_line()`, `stat_quant_line()` and `stat_quant_band()` to
    that they do the model fit consistently using a shared helper function.
-   Edits to package documentation.
-   Add on-line only article _Major axis regression_.
-   Add on-line only article _Mixture Models_. (draft.)
-   Add examples of fitted linear splines to on-line only article 
    _Custom Polynomial Models_.

# ggpmisc 0.6.2

A significant new feature in this release is the support of additional model
fitting functions, both explicitly and by handling missing methods and values 
more gracefully. Another important enhancement is a more flexible approach to
the filtering of peaks and valleys using height and depth thresholds, which 
improves the detection of prominent or major (true?) peaks in noisy data by 
reducing or preventing "false positives".

-   Check compatibility with 'ggplot2' 4.0.0.
-   In `stat_poly_line()` and `stat_poly_eq()` a fitted model object of an 
unexpected class triggers a warning instead of an error.
-   Support `MASS::lqs()`, `nlme::gls()`, `robustbase::lmrob()` and 
`robustbase::lstReg()` in `stat_poly_line()`, `stat_poly_eq()`, 
`stat_fit_deviations()`, `stat_fit_residuals()` and `stat_fit_fitted()`.
-   Support `nlme::gls()`, `MASS::lqs()`, `robustbase::lmrob()`, 
`robustbase::ltsReg()` and model fit objects of classes for which method
`weights()` is not available in `stat_fit_deviations()`, `stat_fit_fitted()`,
`stat_fit_residuals()`.
-   If `predict()` is not available for a `method`, function `stat_poly_line()`
uses `fitted()` instead.
-   Code breaking change in `stat_fit_deviations()`: consistently return prior 
weights in variable `weights` and in new variable `robustness.weights` for the 
implicit weights computed by robust fit methods.
-   Bug fix: the value of 'method.label' not always set.
-   Update `scale_x_logFC()`and `scale_y_logFC()` for improved compatibility
with 'ggplot2' (>= 3.5.2).
-   Implement a local (within-window span) threshold for peak height and valley
depth in `stat_peaks()` and `stat_valleys()`, using parameters `local.threshold`
and `local.reference`.
-   **Code breaking:** Rename parameter `ignore_threshold` into 
`global.threshold` in `find_peaks()`, `stat_peaks()`  and `stat_valleys()` 
for naming consistency and clarity.
-   The scaling applied to user-supplied values for `global.threshold` and 
`local.threshold` can be controlled by passing a `character` argument to 
`threshold.scaling`. Non-scaled thresholds are also supported.
-   Support repulsive geoms from 'ggrepel' in `stat_peaks()` and 
`stat_valleys()` by making extraction of rows conditional.
-   Add HTML Cheat Sheet.
-   Add articles _Custom Polynomial Models_ and _Peaks and Valleys_ as on-line 
only documentation.

# ggpmisc 0.6.1

-   Fix warning with current 'broom' and upcoming 'ggplot2'.
-   Make order of formal parameters in stats consistent with that in current 
'ggplot2'.

# ggpmisc 0.6.0-1

-   Add ellipsis parameter (`...`) to `use_label()` so that in addition to a 
character vector of label names passed to parameter `labels`, separate strings
for each name are now also accepted.
-   Support decreasing-power order of polynomial terms in the labels generated
by `stat_poly_eq()`, `stat_quant_eq()` and `stat_ma_eq()` (not in the input!).
-   In `stat_quant_eq()` return new `qtl.label` for quantiles, separately from 
`grp.label`, which now works only based on a pseudo aesthetic, as in 
`stat_poly_eq()` and `stat_ma_eq()`. **This is a soft code breaking change 
affecting the rendering of model equation labels in some plots.**
-   Define function `check_poly_formula()` and use it in `stat_poly_eq()` and 
`stat_quant_eq()` to validate that the user-supplied model formula is a 
polynomial with terms in order of increasing powers, except when 
`output.type = "numeric"`. If not validated, `NA` is returned as formatted 
character string for the equation label. 
-   Statistics `stat_poly_eq()`, `stat_ma_eq()`, `stat_quant_eq()`,
`stat_correlation()`, and `stat_multcomp()` were in part reimplemented, 
introducing small visual changes in the formatting of labels, including changes
in the default number of digits in very few cases.
-   Export the new utility functions now used internally for formatting 
parameter estimates into character strings in `stat_poly_eq()`, `stat_ma_eq()`, 
`stat_quant_eq()`, `stat_correlation()`, and `stat_multcomp()`.
-   Implement R options `ggpmisc.small.p`, `ggpmisc.small.r` and 
`ggpmisc.decreasing.poly.eq`. Obey R option "verbose" by displaying additional
informative messages.
-   Allow user-defined fit methods passed as argument to `stat_poly_eq()`, 
`stat_poly_line()`, `stat_ma_eq()`, `stat_ma_line()`, `stat_quant_eq()`, 
`stat_quant_line()`, and `stat_quant_band()` to return an atomic `NA` or a
length zero object to skip labelling or plotting related to the attempted model
fit.
-   The redundant, and for a long time deprecated formal parameters 
`label.x.npc` and `label.y.npc` have been removed. **This is a code breaking
change, preceded by a long deprecation period.** _To update broken code, simply
replace `label.y.npc` by `label.y` and `label.x.npc` by `label.x` in the call 
still passing the same arguments._
-   Fix bug in tests of availability of suggested package 'broom'.

# 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()`: **warning** issued by `mvtnorm::pmvnorm()` 
because of convergence failure in Tukey contrasts in case of grouping factors
with more than approximately 5 to 7 levels. Convergence failure also meant
slightly different _P_-values returned in different runs in these cases.
-   Fix bug in `stat_multcomp()`: off-plot letter labels with Tukey contrasts
in some plots with more than five groups.

# ggpmisc 0.5.5

-   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

-   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

-   Fix bug caused by the use of `base::isa()` which is not supported for 
`"formula"` in R < 4.1.0 (reported by Johnny Le).
-   Fix bug in `stat_peaks()` and `stat_valleys()` that made peak and valley 
labels for datetime variables mapped to _x_ to be always formatted in the local 
system's timezone instead of in the timezone of the _x_ scale of the ggplot.
-   Fix bug in `stat_poly_eq()`, `stat_ma_eq()`, `stat_quant_eq()`, and 
`stat_correlation()` that caused some labels not to obey R option `OutDec`. 
(Problem described at Stackoverflow.)

# ggpmisc 0.5.1

-   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

-   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), &tau;
(Kendall's rank correlation) and &rho; (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<sup>2</sup> to the values and labels returned
by `stat_poly_eq()` (implemented using package 'confintr').
-   Add &theta; (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

-   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

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

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

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

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

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

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

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
    `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

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

-   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.

# ggpmisc 0.3.8-1

-   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

-   **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

-   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*.

# ggpmisc 0.3.6

-   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'.

# ggpmisc 0.3.5

-   Add support for "table themes" to geom_table() and
    `geom_table_npc()`.

# ggpmisc 0.3.4

-   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

-   Fix bug in `stat_poly_eq()`.
-   Minor revision of the *User Guide* and documentation.

# ggpmisc 0.3.2

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.

# ggpmisc 0.3.1

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.

# ggpmisc 0.3.0

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 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

-   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_group()` 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()`.

# ggpmisc 0.2.15

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

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

# ggpmisc 0.2.13

-   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

-   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

-   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

-   Add support for *tikz* in `stat_poly_eq()`.
-   Fix bug in `stat_poly_eq()`.
-   Fix bug in `geom_debug_group()`.
-   Fix bug in `stat_fit_augment()`.

# ggpmisc 0.2.8

-   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

-   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_group()`, a geom that summarizes its data input to the
    console, and produces no visible graphical output.

# ggpmisc 0.2.6

-   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

-   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

-   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).

# ggpmisc 0.1.0

*First version.*

-   Add `stat_poly_eq()`
-   Add `stat_debug()`
