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Update README
Signed-off-by: Yuan Tang <[email protected]>
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Diff for: .Rbuildignore

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^.*\.Rproj$
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^\.Rproj\.user$
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^\.travis\.yml$
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^README\.rst$
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^README\.md$
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^vignettes/rsconnect/.*$
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^\.httr-oauth$
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^cran-comments\.md$

Diff for: R/fortify_surv.R

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varying.names <- c('n.risk', 'n.event', 'pstate', 'std.err', 'upper', 'lower')
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varying.i <- lapply(varying.names, function(x) which(startsWith(colnames(d), x)))
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d <- reshape(d, varying = varying.i, v.names = varying.names, timevar = NULL, direction = 'long')
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d <- subset(d, select = -c(id))
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d <- suppressWarnings(subset(d, select = -c(id)))
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rownames(d) <- NULL
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if (length(model$states) > 1) {

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**Note**: This package has been maintained by [@terrytangyuan](https://github.com/terrytangyuan) since 2015. Please [consider sponsoring](https://github.com/sponsors/terrytangyuan)!
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[![cran](http://www.r-pkg.org/badges/version/ggfortify)](https://CRAN.R-project.org/package=ggfortify)
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[![download](https://cranlogs.r-pkg.org/badges/grand-total/ggfortify)](https://CRAN.R-project.org/package=ggfortify)
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# ggfortify
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This package offers ``fortify`` and ``autoplot`` functions to allow automatic ``ggplot2`` to visualize statistical result of popular R packages. Check out our [R Journal paper] (https://journal.r-project.org/archive/2016-2/tang-horikoshi-li.pdf) for more details on the overall architecture design and a gallery of visualizations created with this package. Also check out [autoplotly package](https://github.com/terrytangyuan/autoplotly) that could automatically generate interactive visualizations with [plotly.js](https://plot.ly/) style based on ``ggfortify``. The generated visualizations can also be easily extended using ``ggplot2`` syntax while staying interactive.
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## Installation
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- Install the latest stable release from CRAN:
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```
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install.packages('ggfortify')
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```
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- Install the development version from Github:
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```
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if (!require("remotes")) install.packages("remotes")
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remotes::install_github('sinhrks/ggfortify')
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```
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## Examples
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* [Concepts and Basics of ggfortify](https://cran.r-project.org/web/packages/ggfortify/vignettes/basics.html)
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* [Plotting Diagnostics for LM and GLM with ggplot2 and ggfortify](https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_lm.html)
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* [Plotting Time Series with ggplot2 and ggfortify](https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_ts.html)
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* [Plotting PCA, clustering, LFDA and MDS](https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_pca.html)
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* [Plotting Survival Curves using ggplot2 and ggfortify](https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_surv.html)
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* [Plotting Probability Distributions with ggplot2 and ggfortify](https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_dist.html)
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* [Automatic Generation of Interactive Visualizations in ggplot2 and plotly Styles](https://terrytangyuan.github.io/2018/02/12/autoplotly-intro/)
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* [一行R代码实现繁琐的可视化](http://terrytangyuan.github.io/2015/11/24/ggfortify-intro/)
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## Reference/Citation
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To cite ggfortify in publications, please use (available via ``citation("ggfortify")``):
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```
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Yuan Tang, Masaaki Horikoshi, and Wenxuan Li (2016). ggfortify: Unified Interface to Visualize
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Statistical Result of Popular R Packages. The R Journal, 8.2, 478-489.
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Masaaki Horikoshi and Yuan Tang (2016). ggfortify: Data Visualization Tools for Statistical
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Analysis Results. https://CRAN.R-project.org/package=ggfortify
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```
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## Coverage
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This covers following classes:
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- ``base::matrix``
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- ``base::table`` (supports ``fortify`` only)
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- ``cluster::clara``
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- ``cluster::fanny``
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- ``cluster::pam``
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- ``cluster::silhouette``
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- ``changepoint::cpt``
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- ``fGarch::fGARCH``
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- ``forecast::bats``
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- ``forecast::forecast``
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- ``forecast::ets``
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- ``forecast::nnetar``
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- ``fracdiff::fracdiff``
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- ``glmnet::cv.glmnet``
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- ``glmnet::glmnet``
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- ``KFAS::KFS``
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- ``KFAS::signal`` (inference)
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- ``lfda::lfda``
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- ``lfda::klfda``
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- ``lfda::self``
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- ``maps::map``
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- ``MASS::isoMDS`` (inference)
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- ``MASS::sammon`` (inference)
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- ``raster::RasterBrick``
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- ``raster::RasterCommon``
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- ``raster::RasterLayer``
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- ``raster::RasterStack``
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- ``ROCR::performance``
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- ``sp::Line``
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- ``sp::Lines``
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- ``sp::Polygon``
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- ``sp::Polygons``
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- ``sp::SpatialLines``
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- ``sp::SpatialLinesDataFrame``
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- ``sp::SpatialPoints``
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- ``sp::SpatialPointsDataFrame``
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- ``sp::SpatialPolygons``
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- ``sp::SpatialPolygonsDataFrame``
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- ``splines::basis``
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- ``stats::acf``
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- ``stats::ar``
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- ``stats::Arima``
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- ``stats::cmdscale`` (inference)
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- ``stats::decomposed.ts``
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- ``stats::density``
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- ``stats::factanal``
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- ``stats::glm``
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- ``stats::HoltWinters``
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- ``stats::kmeans``
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- ``stats::lm``
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- ``stats::prcomp``
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- ``stats::princomp``
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- ``stats::spec``
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- ``stats::stepfun``
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- ``stats::stl``
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- ``stats::ts``
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- ``survival::survfit``
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- ``survival::survfit.cox``
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- ``survival::survfitms``
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- ``strucchange::breakpoints``
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- ``strucchange::breakpointsfull``
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- ``timeSeries::timeSeries``
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- ``tseries::irts``
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- ``vars::varprd``
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- ``xts::xts``
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- ``zoo::zooreg``
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## Helper Functions
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- ``ggdistribution`` to plot PDF/CDF
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- ``ggcpgram`` to plot ``cpgram``
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- ``ggtsdiag`` to plot ``tsdiag``
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- ``ggfreqplot`` to generalize ``monthplot``

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