ggpmisc0.6.3 package

Miscellaneous Extensions to 'ggplot2'

build_eq.x.rhs

Left and right hand sides of model equations

check_poly_formula

Validate model formula as a polynomial

coef.lmodel2

Extract Model Coefficients

coefs2poly_eq

Format a polynomial as an equation

confint.lmodel2

Confidence Intervals for Model Parameters

distrmix_helper_fun

Helper function for fitting Normal mixture model

fail_safe_formula

Safely extract the formula from an object

FC_format

Formatter for fold change tick labels

FC_name

Fold change- axis labels

find_peaks

Find local or global maxima (peaks) or minima (valleys)

find_spikes

Find spikes

ggpmisc-ggproto

Stat* Objects

ggpmisc-package

ggpmisc: Miscellaneous Extensions to 'ggplot2'

guess_orientation

Guess the orientation from model formula

keep_tidy

Tidy, glance or augment an object keeping a trace of its origin

outcome2factor

Convert numeric ternary outcomes into a factor

plain_label

Format numbers as character labels

poly2character

Convert a polynomial into character string

predict.lmodel2

Model Predictions

quant_helper_fun

Helper function for fitting quantile regression

reverselog_trans

Reverse log transformation

scale_colour_logFC

Colour and fill scales for log fold change data

scale_colour_outcome

Colour and fill scales for ternary outcomes

scale_shape_outcome

Shape scale for ternary outcomes

scale_x_logFC

Position scales for log fold change data

scale_y_Pvalue

Convenience scale for P-values

sprintf_dm

Format numeric values as strings

stat_correlation

Annotate plot with correlation test

stat_distrmix_eq

Predicted equation from distribution mixture model fit

stat_distrmix_line

Predicted line from distribution mixture model fit

stat_fit_augment

Augment data with fitted values and statistics

stat_fit_deviations

Residuals from model fit as segments

stat_fit_glance

One row summary data frame for a fitted model

stat_fit_residuals

Residuals from a model fit

stat_fit_tb

Model-fit summary or ANOVA

stat_fit_tidy

One row data frame with fitted parameter estimates

stat_ma_eq

Equation, p-value, R^2 of major axis regression

stat_ma_line

Predicted line from major axis linear fit

stat_multcomp

Labels for pairwise multiple comparisons

stat_peaks

Local maxima (peaks) or minima (valleys)

stat_poly_eq

Equation, p-value, R2R^2, AIC and BIC of fitted polynomial

stat_poly_line

Predicted line from linear model fit

stat_quant_band

Predicted band from quantile regression fits

stat_quant_eq

Equation, rho, AIC and BIC from quantile regression

stat_quant_line

Predicted line from quantile regression fit

swap_xy

Swap x and y in a formula

symmetric_limits

Expand a range to make it symmetric

typeset_numbers

Typeset/format numbers preserving trailing zeros

use_label

Assemble label and map it

xy_outcomes2factor

Convert two numeric ternary outcomes into a factor

Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Statistics: locate and tag peaks and valleys; label plot with the equation of a fitted polynomial or other types of models including major axis, quantile and robust and resistant regression. Labels for P-value, R^2 or adjusted R^2 or information criteria for fitted models; parametric and non-parametric correlation; label with ANOVA table for fitted models; label with summary table for fitted models; annotations for multiple comparisons with adjusted P-values. Model fit classes for which suitable methods are provided by package 'broom' and 'broom.mixed' are supported as well as user-defined wrappers on model fit functions. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.

  • Maintainer: Pedro J. Aphalo
  • License: GPL (>= 2)
  • Last published: 2025-11-29