ggfortify v0.4.7

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by Yuan Tang View Source

Data Visualization Tools for Statistical Analysis Results

Unified plotting tools for statistics commonly used, such as GLM, time series, PCA families, clustering and survival analysis. The package offers a single plotting interface for these analysis results and plots in a unified style using 'ggplot2'.

Functions in ggfortify

Name	Description
autoplot.basis	Autoplot spline basis instances
autoplot.breakpoints	Autoplot strucchange::breakpoints
autoplot.list	Autoplot list
autoplot.lm	Autoplot stats::lm and stats::glm
autoplot.tsmodel	Autoplot time series models (like AR, ARIMA)
autoplot.varprd	Autoplot vars::varprd
confint.acf	Calcurate confidence interval for stats::acf
autoplot.aareg	Autoplot survival::aareg
autoplot.acf	Autoplot stats::acf. Note to pass `plot = FALSE` to original function to suppress standard plot output
deprecate.warning	Show deprecate warning
fortify.ets	Convert forecast::bats and forecast::ets to data.frame
autoplot.cpt	Autoplot changepoint::cpt
autoplot.cv.glmnet	Autoplot glmnet::cv.glmnet
autoplot.RasterCommon	Autoplot raster::raster
autoplot.SpatialCommon	Autoplot maps::map
autoplot.ggmultiplot	Autoplot ggmultiplot instances. It returns the passed instance as it is.
autoplot.ggplot	Autoplot ggplot instances. It returns the passed instance as it is.
autoplot.map	Autoplot maps::map
fortify.factanal	Convert stats::factanal to data.frame
autoplot.matrix	Plot base::matrix
cbind_wraps	Wrapper for cbind
check_names	Check data names are equal with expected
autoplot.spec	Autoplot stats::spec
autoplot.stepfun	Plot stats::stepfun
apply_facets	Apply facets to to ggplot2::ggplot
as_tibble.basis	Convert a spline basis to a tibble
fortify.list	Convert list to data.frame
fortify.SpatialCommon	Convert sp instances to data.frame.
apply_grid	Apply grid to to ggplot2::ggplot
fortify.matrix	Convert base::matrix to data.frame
fortify.aareg	Convert survival::aareg to data.frame
fortify.forecast	Convert forecast::forecast to data.frame
geom_factory	Factory function to control ggplot2::geom_xxx functions
get.dtindex	Convert ts index to Date vector
autoplot.density	Autoplot stats::density
autoplot.MSM.lm	Autoplot MSwM::MSM.lm
autoplot.glmnet	Autoplot glmnet::glmnet
fortify.acf	Convert stats::acf to data.frame
autoplot.kmeans	Autoplot cluster instances
fortify.glmnet	Convert glmnet::glmnet to data.frame
fortify.kmeans	Convert cluster instances to data.frame
ggfortify	ggfortify
fortify.basis	Convert spline basis instances to data.frame
fortify.lfda	Convert lfda::lfda or lfda::klfda or lfda::self to data.frame
ggfreqplot	Plot seasonal subseries of time series, generalization of stats::monthplot
fortify.spec	Convert stats::spec to data.frame
autoplot.survfit	Autoplot survival::survfit
autoplot.pca_common	Autoplot PCA-likes
autoplot.performance	Autoplot ROCR::performance
autoplot.forecast	Autoplot forecast::forecast
rbind_ts	Rbind original and predicted time-series-like instances as fortified data.frame
autoplot.ts	Autoplot time-series-like
fortify.stepfun	Convert stats::stepfun to data.frame
get.dtindex.continuous	Get Date vector continue to ts index
get.layout	Calcurate layout matrix for ggmultiplot
fortify.MSM.lm	Convert MSwM::MSM.lm to data.frame
ggcpgram	Plots a cumulative periodogram
+,ggmultiplot,ANY-method	Generic add operator for ggmultiplot
ggdistribution	Plot distribution
fortify_map	Convert maps::map to data.frame.
residuals.ar	Calcurate residuals for stats::ar
geom_confint	Connect observations by stairs.
unscale	Backtransform scale-ed object
ggmultiplot-class	An S4 class to hold multiple ggplot2::ggplot instances
post_autoplot	Post process for fortify. Based on ggplot2::qplot
ggtsdiag	Plots time-series diagnostics
show,ggmultiplot-method	Generic show function for ggmultiplot
is_derived_from	Check object is target class, or object is data.frame fortified from target.
is.univariate	Check if Validates number of ts variates
fitted.ar	Calcurate fitted values for stats::ar
support_autoplot	Check if passed object is supported by ggplot2::autoplot
fortify.RasterCommon	Convert raster to data.frame
fortify.density	Convert stats::density to data.frame
flatten	Flatten dataframe contains matrix
fortify.cpt	Convert changepoint::cpt and strucchange::breakpoints to data.frame
fortify.dist	Convert stats::dist to data.frame
fortify.cv.glmnet	Convert glmnet::cv.glmnet to data.frame
fortify.performance	Convert ROCR::performance objects to data.frame
fortify.survfit	Convert survival::survfit to data.frame
fortify.prcomp	Convert stats::prcomp, stats::princomp to data.frame
fortify.varprd	Convert vars::varprd to data.frame
fortify.table	Convert base::table to data.frame
fortify_base	Convert base::table to data.frame
fortify.ts	Convert time-series-like to data.frame
get_geom_function	Factory function to control ggplot2::geom_xxx functions
fortify.tsmodel	Convert time series models (like AR, ARIMA) to data.frame
grid.draw.ggmultiplot	The implemented grid.draw method for ggmultiplot, in order to work with ggsave() properly
ggbiplot	Draw biplot using ggplot2.
plot_confint	Attach confidence interval to ggplot2::ggplot
plot_label	Attach label to ggplot2::ggplot
infer	Infer class name
post_fortify	Post process for fortify.
print,ggmultiplot-method	Generic print function for ggmultiplot
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Vignettes of ggfortify

Name
basics.Rmd
plot_dist.Rmd
plot_lm.Rmd
plot_map.Rmd
plot_pca.Rmd
plot_surv.Rmd
plot_ts.Rmd
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Last month downloads

Details

Type	Package
Date	2019-05-25
URL	https://github.com/sinhrks/ggfortify
BugReports	https://github.com/sinhrks/ggfortify/issues
Encoding	UTF-8
License	GPL-2
VignetteBuilder	knitr
RoxygenNote	6.1.0
NeedsCompilation	no
Packaged	2019-05-25 23:58:41 UTC; yuan.tang
Repository	CRAN
Date/Publication	2019-05-26 05:20:05 UTC

suggests	changepoint , cluster , dlm , fGarch , forecast , ggrepel , glmnet , grDevices , KFAS , knitr , lfda , lintr , mapdata , MASS , MSwM , nlme , raster , ROCR , sp , stats , strucchange , survival , testthat , timeSeries , tseries , utils , vars , xts , zoo
imports	dplyr (>= 0.3) , grid , gridExtra , scales , stringr , tibble , tidyr
depends	ggplot2 (>= 2.0.0) , methods
Contributors	Masaaki Horikoshi, Ryan Thompson, Luciano Selzer, Dario Strbenac, Austin Dickey, Matthias Greni<c3><a9>, Kirill Voronin