V4: Tools for task views

View, download, load and explore task views

As a preliminary, all task views can be read on-line with the instruction:

h_crantv()
# Open the html page of CRAN task views in the browser

RWsearch provides the functions tvdb_down() and tvdb_load() to download a file renamed or load the task views in .GlobalEnv as a list named tvdb. Four functions are available to explore this list: tv_vec(), tvdb_dfr(), tvdb_list(), tvdb_pkgs().

crandb_down(), tvdb_down(), crandb_load(), tvdb_load()

In an empty directory, the two files crandb.rda and tvdb.rda, which are cleaned versions of the files /web/packages/packages.rds and /src/contrib/Views.rds, must be downloaded from CRAN. Once downloaded, the files are automatically loaded with names crandb (a data.frame) and tvdb (a list) in .GlobalEnv. The most recently updated task view can have an older date than the saved date.

crandb_down()
# $newfile
# [1] "crandb.rda saved and loaded. 17672 packages listed between 2006-03-15 and 2021-06-02"

tvdb_down()
# [1] "tvdb.rda saved. tvdb loaded. 41 task views listed between 2015-01-07 and 2021-06-02"

ls()
# [1] "crandb" "tvdb"

If the files already exist in one specific directory, they can be loaded. Here are the numbers for June 2021. We recall the numbers of a previous vignette written in February 2019:

crandb_load(filename = "crandb-2021-0602.rda") 
# "crandb.rda saved and loaded. 17672 packages listed between 2006-03-15 and 2021-06-02"
# "crandb.rda saved and loaded. 13752 packages listed between 2006-03-15 and 2019-02-25"

tvdb_load(filename = "tvdb-2021-0602.rda") 
# tvdb loaded. 41 task views listed between 2015-01-07 and 2021-06-02
# tvdb loaded. 39 task views listed between 2015-01-07 and 2019-02-25

tvdb_vec(), tvdb_dfr()

Functions tv_vec() and tvdb_dfr() list the task views available and their topics.

There were 39 task views in February 2019 and 41 task views in June 2021. The latest two task views are TeachingStatistics and Tracking. The largest task view is Time Series with 326 referred packages, up from 273 in February 2019. Many task views are maintained a minima and list less packages than in February 2019 due to packages archived by CRAN. Task views need to be reconsidered.

tvdb_vec() 

#  [1] "Bayesian"                  "ChemPhys"                  "ClinicalTrials"           
#  [4] "Cluster"                   "Databases"                 "DifferentialEquations"    
#  [7] "Distributions"             "Econometrics"              "Environmetrics"           
# [10] "ExperimentalDesign"        "ExtremeValue"              "Finance"                  
# [13] "FunctionalData"            "Genetics"                  "gR"                       
# [16] "Graphics"                  "HighPerformanceComputing"  "Hydrology"                
# [19] "MachineLearning"           "MedicalImaging"            "MetaAnalysis"             
# [22] "MissingData"               "ModelDeployment"           "Multivariate"             
# [25] "NaturalLanguageProcessing" "NumericalMathematics"      "OfficialStatistics"       
# [28] "Optimization"              "Pharmacokinetics"          "Phylogenetics"            
# [31] "Psychometrics"             "ReproducibleResearch"      "Robust"                   
# [34] "SocialSciences"            "Spatial"                   "SpatioTemporal"     
# [37] "Survival"                  "TeachingStatistics"        "TimeSeries"               
# [40] "Tracking"                  "WebTechnologies"          
>

tvdb_dfr()

#    version    npkgs name                      topic (npkgs in February 2019) 
# 1  2021-05-19 138   Bayesian                  Bayesian Inference (131) 
# 2  2021-02-06  81   ChemPhys                  Chemometrics and Computational Physics  (81)
# 3  2021-03-05  61   ClinicalTrials            Clinical Trial Design, Monitoring, and Analysis (51)
# 4  2021-05-11 106   Cluster                   Cluster Analysis & Finite Mixture Models (111)                            
# 5  2020-08-02  37   Databases                 Databases with R (38)                                                    
# 6  2021-05-27  28   DifferentialEquations     Differential Equations (29)                                              
# 7  2021-05-28 252   Distributions             Probability Distributions (208)                                           
# 8  2021-05-23 144   Econometrics              Econometrics (139)                                                        
# 9  2021-02-16  94   Environmetrics            Analysis of Ecological and Environmental Data (104)                       
# 10 2021-02-25 112   ExperimentalDesign        Design of Experiments (DoE) & Analysis of Experimental Data (124)         
# 11 2020-02-20  24   ExtremeValue              Extreme Value Analysis (24)                                              
# 12 2021-05-05 156   Finance                   Empirical Finance (154)                                                   
# 13 2020-09-08  40   FunctionalData            Functional Data Analysis (40)                                            
# 14 2021-02-25  22   Genetics                  Statistical Genetics (26)                                                
# 15 2020-08-04  34   gR                        gRaphical Models in R (35)                                               
# 16 2015-01-07  40   Graphics                  Graphic Displays & Dynamic Graphics & Graphic Devices & Visualization (41)
# 17 2021-05-27  92   HighPerformanceComputing  High-Performance and Parallel Computing with R (97)                      
# 18 2021-05-25  98   Hydrology                 Hydrological Data and Modeling (86)                                      
# 19 2021-03-21  96   MachineLearning           Machine Learning & Statistical Learning (102)                             
# 20 2020-12-16  23   MedicalImaging            Medical Image Analysis (32)                                              
# 21 2021-04-25 154   MetaAnalysis              Meta-Analysis (104)                                                       
# 22 2021-04-29 164   MissingData               Missing Data (142)                                                        
# 23 2020-05-26  32   ModelDeployment           Model Deployment with R (31)                                             
# 24 2021-03-01 111   Multivariate              Multivariate Statistics (121)                                             
# 25 2021-05-21  55   NaturalLanguageProcessing Natural Language Processing (55)                                         
# 26 2021-05-05 115   NumericalMathematics      Numerical Mathematics (96)                                               
# 27 2021-05-25 132   OfficialStatistics        Official Statistics & Survey Methodology (123)                            
# 28 2021-05-05 136   Optimization              Optimization and Mathematical Programming (127)                           
# 29 2021-05-27  18   Pharmacokinetics          Analysis of Pharmacokinetic Data (12)                                    
# 30 2021-02-25  82   Phylogenetics             Phylogenetics, Especially Comparative Methods (94)                       
# 31 2021-02-24 242   Psychometrics             Psychometric Models and Methods (209)                                     
# 32 2021-05-17  92   ReproducibleResearch      Reproducible Research (59)                                               
# 33 2021-05-28  58   Robust                    Robust Statistical Methods (60)                                          
# 34 2020-12-11  78   SocialSciences            Statistics for the Social Sciences (82)                                  
# 35 2021-05-20 184   Spatial                   Analysis of Spatial Data (194)                                            
# 36 2021-05-26  92   SpatioTemporal            Handling and Analyzing Spatio-Temporal Data (65)                         
# 37 2021-05-28 251   Survival                  Survival Analysis (264)                                                   
# 38 2020-11-22  45   TeachingStatistics        Teaching Statistics (NA)                                                 
# 39 2021-06-02 326   TimeSeries                Time Series Analysis (273)                                                
# 40 2021-05-26  49   Tracking                  Processing and Analysis of Tracking Data (NA)                            
# 41 2021-05-15 204   WebTechnologies           Web Technologies and Services (247)

tvdb_list(), tvdb_pkgs()

tv_list() lists all task view packages. tvdb_dfr() lists the packages of the task views selected by the user.

tvdb_list()

# $Bayesian
# [1]   "abc"      "abn"      "AdMit"    "arm"      "AtelieR"  
# ...
# [127] "spTimer"  "ssgraph"  "stochvol" "tgp"      "zic"     
# ...
# ...
# $WebTechnologies
# [1]   "abbyyR"    "ajv"       "analogsea" "aRxiv"     "aws.polly" 
# ...
# [243] "xslt"      "yhatr"     "yummlyr"   "zendeskR"  "ZillowR"

tvdb_pkgs(ChemPhys, Distributions, Robust)

# $ChemPhys
#  [1] "ALS"               "AnalyzeFMRI"       "AquaEnv"           "astro"
# ...
# [89] "varSelRF"          "webchem"           "WilcoxCV"
#
# $Distributions
#   [1] "actuar"           "AdMit"             "agricolae"         "ald"
# ...
# [205] "visualize"        "Wrapped"           "zipfextR"          "zipfR"
#
# $Robust
#  [1] "cluster"        "complmrob"      "covRobust"      "coxrobust"      "distr"
# ...
# [56] "ssmrob"         "tclust"         "TEEReg"         "walrus"         "WRS2"

Counting the number of referred packages

The largest task view has referred 326 packages (273 in February 2019). All task views have referred 4298 (4021) packages but only 3451 (3221) unique packages. This is 19.5 % (down from 23.4 % in 2019) of the total number of packages currently in CRAN. The task is immense if we want to refer all packages.

nrow(crandb)
# 17672 (13752)

max(sapply(tvdb_list(), length))
# [1] 326 (273)

length(unlist(tvdb_list()))
# [1] 4298 (4021)

length(unique(unlist(tvdb_list())))
# [1] 3451 (3221)

Task view maintenance

RWsearch focuses on detecting the (old and new) packages that could be added to the task views.

Function s_crandb_tvdb() combines many functions of RWsearch. It searchs packages in crandb by keywords and checks if the found packages are referred in the selected task view and installed in the computer (in the /site-library directory).

The example presented below refers to the Distributions task view.

s_crandb_tvdb()

The output of s_crandb_tvdb() is a list with the following items:

spkgs: packages that match the keywords.
inTV: packages that are already referred in the selected task view.
notinTV: packages that are not (yet) referred in the task view.
inTV_in: packages that are referred and installed in the computer.
inTV_un: packages that are referred but not installed in the computer.
notinTV_in: packages that are not referred and installed in the computer.
notinTV_un: packages that are neither referred nor installed in the computer.

keywords <- cnsc(probability, distribution)
(lst <- s_crandb_tvdb(char = keywords, tv = "Distributions", 
                      from = -15, to = "2019-02-25", select = "PT"))

# $spkgs
# [1] "distreg.vis" "GB2group"    "ipcwswitch"  "MixGHD"      "MSPRT"       "pgdraw"     
# [7] "philentropy" "triangle"   

# $inTV
# [1] "triangle"

# $notinTV
# [1] "distreg.vis" "GB2group"    "ipcwswitch"  "MixGHD"      "MSPRT"       "pgdraw"     
# [7] "philentropy"

# $inTV_in
# character(0)

# $inTV_un
# [1] "triangle"

# $notinTV_in
# character(0)

# $notinTV_un
# [1] "distreg.vis" "GB2group"    "ipcwswitch"  "MixGHD"      "MSPRT"       "pgdraw"     
# [7] "philentropy"

Visualize the unreferred packages

A first assesment of the packages that match the keywords can be done with p_table2(). Consider also p_display5() to read the results in the browser.

p_table2(), p_display5()

p_table2(lst$notinTV)

#      Package     Title                                                                                                                     
# 2766 distreg.vis Framework for the Visualization of Distributional Regression Models                                                       
# 4209 GB2group    Estimation of the Generalised Beta Distribution of the Second Kind from Grouped Data                                      
# 5592 ipcwswitch  Inverse Probability of Censoring Weights to Deal with Treatment Switch in Randomized Clinical Trials                      
# 7072 MixGHD      Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions
# 7404 MSPRT       Modified Sequential Probability Ratio Test (MSPRT)                                                                        
# 8613 pgdraw      Generate Random Samples from the Polya-Gamma Distribution                                                                 
# 8659 philentropy Similarity and Distance Quantification Between Probability Functions

p_display5(lst$notinTV)
## read the html page launched in your browser

From this list and the DESCRIPTION in the html page, packages GB2group, MixGHD, pgdraw and philentropy deserve further exploration.

p_page(), p_pdfweb()

4 packages is a reasonnable number. We can open the CRAN/index.html pages and CRAN/manual.pdf files in the browser. Alternatively, consider downloading the documentation of these packages.

pkgs <- cnsc(GB2group, MixGHD, pgdraw, philentropy)

p_page(char = pkgs)
## read the 4 html pages launched in your browser

p_pdfweb(char = pkgs)
## read the 4 pdf pages launched in your browser

p_down(char = pkgs)
## read the files saved in the current directory

The pdf files and the vignettes give all expected information:

GB2group uses the generalized beta distribution of the second kind inplemented in the GB2 package which is already referred in the task view. There is no need to mention it.
MixGHD implements three d,p,q,r functions: dpqrGHD(), dpqrCGHD(), dpqrMSGHD(). This package will be referred in the task view.
pgdraw generates random samples from the Polya-Gamma distribution by using a function in a non-standard format: pgdraw() rather than something like rpg(). This is probably to avoid some duplicate with the BayesLogit::rpg() function provided by the BayesLogit package. Discussion is open.
Philentropy does not include any d,p,q,r functions but calculates some distances between distributions. This is a connex topic with a special section in the task view. The package will be added to the task view.

For these packages, the quality of the d,p,q,r functions should be explored (but has not been yet).