Package overview

ggpmisc-package

ggpmisc: Miscellaneous Extensions to 'ggplot2'

Plot creation

Additional ggplot methods

ggplot(<ts>) ggplot(<xts>)

Create a new ggplot plot from time series data

Geoms

Geoms, short for geometric objects, describe the type of plot you will produce.

geom_table()

Tables

Statistics

It is often useful to summarize spectral data before plotting, and that is what these transformations do.

stat_peaks() stat_valleys()

Local maxima (peaks) or minima (valleys)

stat_poly_eq()

Equation, p-value, R^2, AIC or BIC of fitted polynomial

stat_fit_tb()

Model-fit summary or ANOVA

stat_fit_tidy()

One row data frame with fitted parameter estimates

stat_fit_glance()

One row summary data frame for a fitted model

stat_fit_augment()

Augment data with fitted values and statistics

stat_fit_deviations()

Residuals from model fit as segments

stat_fit_residuals()

Residuals from a model fit

stat_dens2d_filter() stat_dens2d_filter_g()

Filter observations by local density

stat_dens2d_labels()

Reset labels of observations in high density regions

stat_quadrant_counts()

Number of observations in quadrants

stat_fmt_tb()

Select and slice a tibble nested in data

Fortify or Try

Convert R objects containing observations in other formats into ‘tibble’ objects suitable for plotting.

try_data_frame() try_tibble()

Convert an R object into a tibble

Changes

Objects moved to package ‘gginnards’ and no longer exported from ‘ggpmisc’.

stat_quadrat_counts

Renamed to stat_quadrant_counts

Moved

Moved to package 'gginnards'