From 5c45aa9c90f9de0b499a7b4e76ef966e76ed19f3 Mon Sep 17 00:00:00 2001 From: Martin Monkman Date: Sat, 3 Aug 2019 08:50:05 -0700 Subject: [PATCH] package reference to #### `{}` --- 03_data_science_practice.Rmd | 6 ++--- 04_using_R.Rmd | 7 +++--- 13_api.Rmd | 2 +- 15_anonymity_confidentiality.Rmd | 16 ++++++++------ 21_data_reading_fileformat.rmd | 16 +++++++------- 40_data_visualization.Rmd | 8 +++---- 41_chart_types.Rmd | 20 ++++++++++++----- 50_quantitative_methods.Rmd | 8 ++++--- 51_bayesian.Rmd | 8 +++---- 52_machine_learning.Rmd | 8 ++++--- 53_regression.Rmd | 16 +++++++------- 54_time_series.Rmd | 20 ++++++++--------- 59_quantitative_methods_2.Rmd | 38 ++++++++++++++++---------------- 13 files changed, 95 insertions(+), 78 deletions(-) diff --git a/03_data_science_practice.Rmd b/03_data_science_practice.Rmd index c5063a3..8806b6c 100644 --- a/03_data_science_practice.Rmd +++ b/03_data_science_practice.Rmd @@ -114,7 +114,7 @@ Emily Robinson, [Red Flags in Data Science Interviews](http://hookedondata.org/R ## R packages supporting robust workflow -### {janitor} - +### `{janitor}` [{janitor}](sfirke.github.io/janitor/index.html) -- "has simple functions for examining and cleaning dirty data. It was built with beginning and intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff." @@ -123,7 +123,7 @@ CRAN: [janitor: Simple Tools for Examining and Cleaning Dirty Data](https://cran GitHub: [sfirke/janitor](https://github.com/sfirke/janitor) -### {packrat} - +### `{packrat}` [{Packrat} is a dependency management system for R](http://rstudio.github.io/packrat/) @@ -137,7 +137,7 @@ GitHub: [rstudio/packrat](https://github.com/rstudio/packrat) Miles McBain (2019-04-09) [A workflow for lightweight R dependency management](https://milesmcbain.xyz/packrat-lite/) -### {usethis} - +### `{usethis}` "usethis is a workflow package: it automates repetitive tasks that arise during project setup and development, both for R packages and non-package projects" diff --git a/04_using_R.Rmd b/04_using_R.Rmd index 87830f0..6faa90b 100644 --- a/04_using_R.Rmd +++ b/04_using_R.Rmd @@ -74,7 +74,7 @@ Jessica Minnier, 2019-07-29, [Sharpening the Tools in Your Data Science Toolbox] ### The R-Python interface -#### {feather} +#### `{feather}` {feather} is designed to read and write feather files, a lightweight binary columnar data store designed for maximum speed. There is a [parallel Python package](https://github.com/wesm/feather). @@ -85,7 +85,7 @@ Jessica Minnier, 2019-07-29, [Sharpening the Tools in Your Data Science Toolbox] -#### {reticulate} +#### `{reticulate}` The reticulate package provides a comprehensive set of tools for interoperability between Python and R. @@ -100,13 +100,14 @@ The reticulate package provides a comprehensive set of tools for interoperabilit -#### {rpy2} +#### `{rpy2}` JD Long, twitter thread on {rpy2} documentation: [twitter thread](https://twitter.com/CMastication/status/1157645891672707072?s=20) + *** ## The R community diff --git a/13_api.Rmd b/13_api.Rmd index b514583..3cf1370 100644 --- a/13_api.Rmd +++ b/13_api.Rmd @@ -34,7 +34,7 @@ Jose Gonzalez, [Using Google Maps API and R](https://gist.github.com/josecarlosg ### Packages -#### `httr` +#### `{httr}` CRAN: [httr: Tools for Working with URLs and HTTP](https://cran.r-project.org/package=httr/) diff --git a/15_anonymity_confidentiality.Rmd b/15_anonymity_confidentiality.Rmd index 84bd428..2ef5f4c 100644 --- a/15_anonymity_confidentiality.Rmd +++ b/15_anonymity_confidentiality.Rmd @@ -182,9 +182,9 @@ Meghan O’Malley, Lawrence R. Ernst, ["Practical Considerations in Applying the John Mount (1012) ["Modeling Trick: Masked Variables"](http://www.win-vector.com/blog/2012/07/modeling-trick-masked-variables/) -### **sdcMicro** +### `{sdcMicro}` -`sdcMicro` is the best available SDC tool I have found in the R space, so I've given it top-billing rather than my usual alpabetical listing. +{sdcMicro} is the best available SDC tool I have found in the R space, so I've given it top-billing rather than my usual alpabetical listing. **package** @@ -209,7 +209,7 @@ Daniel Abril, Guillermo Navarro-Arribas and Vicenç Torra (2015) ["Data Privacy -### **sdcMicroGUI** +### `{sdcMicroGUI}` **package** @@ -221,12 +221,12 @@ Matthias Templ, Bernhard Meindl and Alexander Kowarik, [Tutorial for sdcMicroGUI -### **sdcTable** +### `{sdcTable}` CRAN page: [sdcTable: Methods for Statistical Disclosure Control in Tabular Data](https://cran.r-project.org/package=sdcTable) -### **easySdcTable** +### `{easySdcTable}` ** package** @@ -236,7 +236,7 @@ vignette: [`easySdcTable` Vignette](https://cran.r-project.org/package=easySdcTa -### **digest** +### `{digest}` **package** @@ -248,7 +248,7 @@ Jan Górecki (2014), ["Data anonymization in R"](https://jangorecki.github.io/bl * [alternate source](https://www.r-bloggers.com/data-anonymization-in-r/) -### **obfuscateR** +### `{obfuscateR}` (Note: this package has not been submitted to CRAN, and is clearly in development/stalled) @@ -263,3 +263,5 @@ github page: [PedramNavid/obfuscateR](https://github.com/PedramNavid/obfuscateR) Benjamin Bengfort, ["A Practical Guide to Anonymizing Datasets with Python & Faker: How Not to Lose Friends and Alienate People"](http://blog.districtdatalabs.com/a-practical-guide-to-anonymizing-datasets-with-python-faker), 2016 + +-30- diff --git a/21_data_reading_fileformat.rmd b/21_data_reading_fileformat.rmd index e6d0fef..4ae9ddf 100644 --- a/21_data_reading_fileformat.rmd +++ b/21_data_reading_fileformat.rmd @@ -23,7 +23,7 @@ In particular, survey data [R database interfaces](http://www.burns-stat.com/r-database-interfaces/) -### {rio} - +### `{rio}` **package** @@ -33,7 +33,7 @@ vignette: [Import, Export, and Convert Data Files](https://cran.r-project.org/pa -### {googledrive} - +### `{googledrive}` **package** @@ -43,7 +43,7 @@ tidyverse page: [`googledrive`](https://tidyverse.github.io/googledrive/) -### {foreign} - +### `{foreign}` **package** @@ -54,7 +54,7 @@ CRAN page: [foreign: Read Data Stored by Minitab, S, SAS, SPSS, Stata, Systat, W * [How to open an SPSS file into R](http://www.milanor.net/blog/how-to-open-an-spss-file-into-r/), by Davide Massidda (2014-03-26) -### {haven} - +### `{haven}` **package** @@ -70,14 +70,14 @@ Luis D. Verde, 2018-12-14, [Tidyeval meets PDF table hell](http://luisdva.github ## Stata files -### {read.dta} - +### `{read.dta}` Reads a file in Stata version 5–12 binary format into a data frame. CRAN page: [`read.dta`: Read Stata Binary Files](http://stat.ethz.ch/R-manual/R-devel/library/foreign/html/read.dta.html) -### {readstata13} - +### `{readstata13}` Function to read and write the 'Stata' file format. @@ -87,13 +87,13 @@ CRAN Page: [readstata13: Import 'Stata' Data Files](readstata13: Import 'Stata' ## Time series database files -### {TSdbi} and related packages +### `{TSdbi}` and related packages **package** CRAN page: [TSdbi: Time Series Database Interface]( https://CRAN.R-project.org/package=TSdbi) -Note: `TSdbi` has some related extension packages: +Note: {TSdbi} has some related extension packages: * CRAN page: [TSdata: 'TSdbi' Illustration](https://cran.r-project.org/package=TSdata) * This package gives an overview and usage examples for all the `TSdbi` family of packages diff --git a/40_data_visualization.Rmd b/40_data_visualization.Rmd index 81b168e..57c4f08 100644 --- a/40_data_visualization.Rmd +++ b/40_data_visualization.Rmd @@ -129,7 +129,7 @@ Medium's [Data Visualization Society](https://medium.com/data-visualization-soci -## {ggplot2] -- the pre-eminent way to create charts and graphs in R +## `{ggplot2}` -- the pre-eminent way to create charts and graphs in R * [{ggplot2}: part of the tidyverse](http://ggplot2.tidyverse.org/index.html) -- reference materials, examples, etc etc. Start here. @@ -157,7 +157,7 @@ There are many extension packages that allow you to make other visualizations in * Gallery of {ggplot2} extensions: [ggplot2-exts.org/gallery/]({ggplot2} extensions - gallery ) -#### {ggfittext} +#### `{ggfittext}` "ggplot2 geoms to fit text into boxes" @@ -197,7 +197,7 @@ Colour is a vital part of good data visualization; the following links support t * [R color cheatsheet](https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/colorPaletteCheatsheet.pdf) -### {colorspace} +### `{colorspace}` "A Toolbox for Manipulating and Assessing Colors and Palettes" @@ -220,7 +220,7 @@ Cynthia A. Brewer, Geoffrey W. Hatchard, and Mark A. Harrower (2003) ColorBrewer -#### the R package [{RColorBrewer}]() +#### the R package `{RColorBrewer}` * [RColorBrewer's Palettes](https://www.r-graph-gallery.com/38-rcolorbrewers-palettes/) from The R Graph Gallery diff --git a/41_chart_types.Rmd b/41_chart_types.Rmd index 2c3c44f..ff9be80 100644 --- a/41_chart_types.Rmd +++ b/41_chart_types.Rmd @@ -91,7 +91,7 @@ A.K.A. bar and line graphs. Don't use them! ## Genealogical data -Package: {ggeneology} +#### `{ggeneology}` * Lindsay Rutter, Susan VanderPlas, Dianne Cook, Michelle A. Graham (2019) ["ggenealogy: An R Package for Visualizing Genealogical Data"](https://www.jstatsoft.org/article/view/v089i13), _Journal of Statistical Software_, Vol 89 (13) @@ -140,7 +140,7 @@ Haley Jeppson and Heike Hofmann (2018-09-12) [Mosaic plots with ggplot2](https:/ Hadley Wickham and Heike Hofmann, ["Product Plots"][@Wickham-Hofmann_2011] -[Mosaic or Marimekko charts](https://learnr.wordpress.com/2009/03/29/ggplot2_marimekko_mosaic_chart/) (in ggplot2) +[Mosaic or Marimekko charts](https://learnr.wordpress.com/2009/03/29/ggplot2_marimekko_mosaic_chart/) (in {ggplot2}) Perceptual Edge, [A Design Problem](https://www.perceptualedge.com/example13.php) @@ -153,8 +153,11 @@ Alberto Cairo (2019-07-09) [A mosaic plot that exemplifies good design practices ## Network graphs +#### `{DiagramR}` + {DiagramR}: Graph and network visualization using tabular data in R + * [github repo](https://github.com/rich-iannone/DiagrammeR) * CRAN page: [DiagrammeRsvg: Export DiagrammeR Graphviz Graphs as SVG](https://cran.r-project.org/package=DiagrammeRsvg) @@ -182,7 +185,7 @@ Lauren Boucher (2016-03-10) [What are the different types of population pyramids [Population Pyramids for Select Canadian Provinces, 2015-2035](https://github.com/atheriel/visualizations/tree/master/provincial-demography) -* uses `ggplot2` to create pyramids +* uses {ggplot2} to create pyramids [Simpler population pyramid in ggplot2](https://stackoverflow.com/questions/14680075/simpler-population-pyramid-in-ggplot2) @@ -219,7 +222,10 @@ acarioli (2016-01-11) [Population pyramids in ggplot](https://aledemogr.wordpres ** ridgeline plots in R ** -[`ggridges` package by Claus Wilke](https://cran.r-project.org/package=ggridges) -- CRAN page + +#### `{ggridges}` + +[{ggridges} package by Claus Wilke](https://cran.r-project.org/package=ggridges) -- CRAN page Alex Whan, 2016-03-24, [ggplot2 and Joy Division](http://alexwhan.com/2016-03-24-joy-division-plot) - at Incrutable Errors @@ -259,7 +265,7 @@ Cole Nussbaumer Knaflic, 2015, _Storytelling with Data_, pp.47-49. Kyle Walker, 2015-05-17, [Global population change with a slopegraph in ggplot2](https://rpubs.com/walkerke/slopegraph) -### `slopegraph` +#### `{slopegraph}` [github](https://github.com/leeper/slopegraph) @@ -269,6 +275,8 @@ Kyle Walker, 2015-05-17, [Global population change with a slopegraph in ggplot2] ## Ternary plots +#### `{ggtern}` + [`ggtern` - an extension to `ggplot2`](http://www.ggtern.com/) for plotting ternary diagrams. @@ -276,6 +284,8 @@ Kyle Walker, 2015-05-17, [Global population change with a slopegraph in ggplot2] ## Waffle plots +#### `{waffle}` + **Package** CRAN page: [waffle: Create Waffle Chart Visualizations in R](https://cran.r-project.org/package=waffle) diff --git a/50_quantitative_methods.Rmd b/50_quantitative_methods.Rmd index 7545e0a..33106cf 100644 --- a/50_quantitative_methods.Rmd +++ b/50_quantitative_methods.Rmd @@ -62,7 +62,7 @@ Martin Monkman, 2013-12-01, ["A few random things"](http://bayesball.blogspot.ca [correlated random variables: a gist](https://gist.github.com/MonkmanMH/a8b58f9cb140d702139b75467806c6d1) -#### Random() {base R} +#### Random() `{base R}` **package** @@ -70,14 +70,14 @@ CRAN page: [Random {base}: Random number generation](http://stat.ethz.ch/R-manua -#### {random} +#### `{random}` **package** CRAN page: [random: True Random Numbers using RANDOM.ORG](https://cran.r-project.org/package=random/) -#### {sampling} +#### `{sampling}` **package** @@ -88,3 +88,5 @@ CRAN page: [sampling: Survey Sampling](https://cran.r-project.org/package=sampli Examples of how the package can be applied + +-30- diff --git a/51_bayesian.Rmd b/51_bayesian.Rmd index 27fd122..afc048a 100644 --- a/51_bayesian.Rmd +++ b/51_bayesian.Rmd @@ -52,7 +52,7 @@ Tarek Amr, ["Experimenting the Bayesian way"](https://www.datascience.com/blog/e Arranged by package -#### {bayestestR} +#### `{bayestestR}` **package** @@ -63,14 +63,14 @@ GitHub page: [bayestestR: Utilities for analyzing Bayesian models and posterior easystats (2019-04-15) [Describe and understand Bayesian models and posteriors using bayestestR](https://easystats.github.io/blog/posts/bayestestr_presentation/) -#### {HydeNet} +#### `{HydeNet}` CRAN: [HydeNet: Hybrid Bayesian Networks Using R and JAGS](https://cran.r-project.org/web/packages/HydeNet/) Vignette: [Decision Network (Influence Diagram) Analyses in HydeNet](https://cran.r-project.org/web/packages/HydeNet/vignettes/DecisionNetworks.html) -#### {rjags} +#### `{rjags}` **package** @@ -81,7 +81,7 @@ CRAN page: [rjags: Bayesian Graphical Models using MCMC](https://cran.r-project. Alicia Johnson: [Bayesian modeling with {rjags}] {link to DataCamp course removed} -#### {tidybayes} +#### `{tidybayes}` **package** diff --git a/52_machine_learning.Rmd b/52_machine_learning.Rmd index 300dc6a..20c9a39 100644 --- a/52_machine_learning.Rmd +++ b/52_machine_learning.Rmd @@ -57,14 +57,14 @@ Khushbu Shah, 2016-06-06, ["What are the Best Machine Learning Packages in R?"]( -### {caret} - +### `{caret}` Jason Brownlee (2016-02-03) [Your First Machine Learning Project in R Step-By-Step](https://machinelearningmastery.com/machine-learning-in-r-step-by-step/) -- at [Machine Learning Mastery](https://machinelearningmastery.com/start-here/) -### {h2o} - +### `{h2o}` **package** @@ -76,8 +76,10 @@ Erin LeDell, 2017, [Automatic Machine Learning in R](https://github.com/h2oai/h2 -### {mlr} - +### `{mlr}` [Machine Learning in R ](https://mlr.mlr-org.com/) + + -30- diff --git a/53_regression.Rmd b/53_regression.Rmd index 9d049ad..aeb04f5 100644 --- a/53_regression.Rmd +++ b/53_regression.Rmd @@ -48,7 +48,7 @@ http://andrewgelman.com/2017/03/04/interpret-confidence-intervals/ ## Packages -#### {broom} +#### `{broom}` CRAN: [broom: Convert Statistical Analysis Objects into Tidy Tibbles](https://cran.r-project.org/package=broom) @@ -59,7 +59,7 @@ CRAN: [broom: Convert Statistical Analysis Objects into Tidy Tibbles](https://cr David Robinson (2015-03-19) [broom: a package for tidying statistical models into data frames](http://varianceexplained.org/r/broom-intro/) -#### {brms} +#### `{brms}` [brms: Bayesian Regression Models using Stan](https://cran.r-project.org/package=brms) @@ -68,13 +68,13 @@ David Robinson (2015-03-19) [broom: a package for tidying statistical models int [github page](https://github.com/paul-buerkner/brms) -##### {brmstools} +##### `{brmstools}` * [tools and helpers for `brms`](https://mvuorre.github.io/brmstools/) -#### {modelr} +#### `{modelr}` [github page](https://github.com/tidyverse/modelr) @@ -102,7 +102,7 @@ University of Virginia Library Research Data Services, ["Getting Started with Qu ### R -#### {quantreg} +#### `{quantreg}` **package** @@ -141,7 +141,7 @@ Paywalled articles: ### R -#### {dominanceanalysis} +#### `{dominanceanalysis}` CRAN page: [dominanceanalysis: Dominance Analysis](https://cran.r-project.org/package=dominanceanalysis/) @@ -151,12 +151,12 @@ CRAN page: [dominanceanalysis: Dominance Analysis](https://cran.r-project.org/pa * Dominance Analysis (Azen and Bodescu), for multiple regression models: OLS (univariate, multivariate), GLM and HLM -#### {relaimpo} +#### `{relaimpo}` CRAN page: [relaimpo: Relative Importance of Regressors in Linear Models](https://cran.r-project.org/package=relaimpo/) -#### {yhat} +#### `{yhat}` CRAN page: [yhat: Interpreting Regression Effects](https://cran.r-project.org/package=yhat/) diff --git a/54_time_series.Rmd b/54_time_series.Rmd index 8557193..7b20d45 100644 --- a/54_time_series.Rmd +++ b/54_time_series.Rmd @@ -37,7 +37,7 @@ Earo Wang, ["Melt the clock: Tidy time series analysis"](https://resources.rstud -#### {tsfeatures} +#### `{tsfeatures}` Methods for extracting various features from time series data @@ -53,7 +53,7 @@ CRAN: [tsfeatures: Time Series Feature Extraction](https://cran.r-project.org/pa -#### {tsibble} +#### `{tsibble}` **package** @@ -68,7 +68,7 @@ Earo Wang, 2018-12-20, ["Reintroducing tsibble: data tools that melt the clock"] Earo Wang and Dianne Cook and Rob J Hyndman, January 2019, "A new tidy data structure to support exploration and modeling of temporal data"[@wang-tsibble-2019] -#### {padr} +#### `{padr}` **package** @@ -79,7 +79,7 @@ CRAN page: [padr: Quickly Get Datetime Data Ready for Analysis](https://cran.r-p Andrew Clark, 2017-07-19, [padr package example](https://www.mytinyshinys.com/2017/07/19/user2017-padr/) -#### {zoo} +#### `{zoo}` **package** @@ -104,7 +104,7 @@ Kamala Kanta Mishra, [Selecting Forecasting Methods in Data Science](http://www. Kostiantyn Kravchuk, ["Forecasting: Time Series Exploration Exercises (Part-1)"](https://www.r-bloggers.com/forecasting-time-series-exploration-exercises-part-1/) (2017-04-10) -#### {fable} +#### `{fable}` "...provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling. Data, model and forecast objects are all stored in a tidy format." @@ -113,7 +113,7 @@ Kostiantyn Kravchuk, ["Forecasting: Time Series Exploration Exercises (Part-1)"] documentation: [`fable`](https://fable.tidyverts.org/) -#### {prophet} +#### `{prophet}` **package** @@ -156,7 +156,7 @@ U.S. Census Bureau, [The X-13ARIMA-SEATS Seasonal Adjustment Program](https://ww ### R -#### {ggseas} +#### `{ggseas}` **package** @@ -173,7 +173,7 @@ Ellis, Peter. 2016-03-28. ["Seasonal decomposition in the ggplot2 universe with Ellis, Peter. 2016-02-08. ["ggseas package for seasonal adjustment on the fly with ggplot2"](http://ellisp.github.io/blog/2016/02/08/ggseas/), blog entry. -#### {seasonal} +#### `{seasonal}` **[seasonal: R-interface to X-13ARIMA-SEATS](http://www.seasonal.website/seasonal.html)** @@ -189,7 +189,7 @@ github page: [christophsax/seasonal](https://github.com/christophsax/seasonal) -#### {x12} +#### `{x12}` **package** @@ -202,7 +202,7 @@ Rytis (2013-02-08) [_Using X12-ARIMA with R_](https://blogs.fsfe.org/rytis/2013/ -#### {x13binary} +#### `{x13binary}` (US Census Bureau X-13, packaged for easy loading. Loads as a dependency for most of the other seasonal adjustment packages.) diff --git a/59_quantitative_methods_2.Rmd b/59_quantitative_methods_2.Rmd index 0bbba55..5e935e8 100644 --- a/59_quantitative_methods_2.Rmd +++ b/59_quantitative_methods_2.Rmd @@ -48,7 +48,7 @@ Michael Stoto ["Ecological Inference in Public Health"](https://www.researchgate Arranged by package -#### {ei} +#### `{ei}` **package** @@ -80,7 +80,7 @@ World Bank (date unknown) ["Measuring Inequality"](http://go.worldbank.org/W2TRR ### R -#### {ineq} +#### `{ineq}` **package** @@ -134,7 +134,7 @@ Thomas Leeper, [Multiple imputation](http://thomasleeper.com/Rcourse/Tutorials/m -#### {Amelia} +#### `{Amelia}` **package** @@ -147,13 +147,13 @@ description: [Amelia II: A Program for Missing Data](http://gking.harvard.edu/am github page for [Amelia II](https://github.com/IQSS/Amelia) -#### {BaBooN} +#### `{BaBooN}` CRAN page: [BaBooN: Bayesian Bootstrap Predictive Mean Matching - Multiple and Single Imputation for Discrete Data](https://cran.r-project.org/package=BaBooN) -#### {Hmisc} +#### `{Hmisc}` **package** @@ -161,7 +161,7 @@ CRAN page: [Hmisc: Harrell Miscellaneous](https://cran.r-project.org/package=Hmi -#### {mi} +#### `{mi}` **package** @@ -174,7 +174,7 @@ Su, Gelman, Hill and Yajima (2011) [Multiple Imputation with Diagnostics (mi) in Ben Goodrich and Jonathan Kropko, 2014-06-16, ["An Example of mi Usage"](https://cran.r-project.org/package=mi/vignettes/mi_vignette.pdf) -#### {mice} +#### `{mice}` **package** @@ -195,7 +195,7 @@ Michy Alice, ["Imputing missing data with R; MICE package"](https://www.r-blogge datascience+, 2015-10-04 and updated 2017-04-28, [Imputing Missing Data with R; MICE package](https://datascienceplus.com/imputing-missing-data-with-r-mice-package/) -#### {missMDA} +#### `{missMDA}` **package** @@ -207,19 +207,19 @@ francoishusson, 2017-08-15, [Multiple imputation for continuous and categorical -#### {missForest} +#### `{missForest}` **package** CRAN page: [missForest: Nonparametric Missing Value Imputation using Random Forest](https://cran.r-project.org/package=missForest) -#### {NPBayesImpute} +#### `{NPBayesImpute}` CRAN page: [NPBayesImpute: Non-Parametric Bayesian Multiple Imputation for Categorical Data](https://cran.r-project.org/package=NPBayesImpute) -#### {VIM} +#### `{VIM}` **package** @@ -239,7 +239,7 @@ https://www.jstatsoft.org/article/view/v074i07 ## Moving Window (for raster data) -### {grainchanger} +### `{grainchanger}` "The grainchanger package provides functionality for data aggregation to a grid via moving-window or direct methods." @@ -256,7 +256,7 @@ https://www.jstatsoft.org/article/view/v074i07 (_Not to be confused with multi_variable_ analysis) -### {explor} +### `{explor}` [GitHub page](https://juba.github.io/explor/) -- "an R package to allow interactive exploration of multivariate analysis results." @@ -339,7 +339,7 @@ DIY Solution * Christopher Waldhauser (2014-04-13) [Survey: Computing Your Own Post-Stratification Weights in R](https://www.r-bloggers.com/survey-computing-your-own-post-stratification-weights-in-r/) (at R-Bloggers) -#### {anesrake} +#### `{anesrake}` **package** @@ -354,7 +354,7 @@ Josh Pasek, Matthew DeBell, Jon A. Krosnick (2014-07-26) ["Standardizing!and!Dem [Raking weights with R](http://sdaza.com/survey/2012/08/25/raking/) -#### {ipfp} +#### `{ipfp}` **package** @@ -367,7 +367,7 @@ github page: [awblocker/ipfp](https://github.com/awblocker/ipfp) [Iterative proportional fitting in R (stackexchange)](http://stats.stackexchange.com/questions/59115/iterative-proportional-fitting-in-r) -#### {survey} +#### `{survey}` **package** @@ -391,7 +391,7 @@ Lumley, Thomas (2010) _Complex Surveys: A Guide to Analysis Using R_, John Wiley [rake {survey}: Raking of replicate weight design](http://faculty.washington.edu/tlumley/old-survey/html/rake.html) -#### {weights} +#### `{weights}` **package** @@ -411,7 +411,7 @@ CRAN page: [weights: Weighting and Weighted Statistics](https://cran.r-project.o Arranged by package -#### {lavaan} +#### `{lavaan}` **package** @@ -426,7 +426,7 @@ Yves Rosseel, 2012-05-24, ["lavaan: An R Package for Structural Equation Modelin Grace Charles, 2015-05-20, [First Steps with Structural Equation Modeling](https://www.r-bloggers.com/first-steps-with-structural-equation-modeling/) -- blog post by Noam Ross, re: Charles' presention at Davis R Users' Group. -#### {sem} +#### `{sem}` **package**