This is a cheatsheet on using R to do data analysis. The main focus is on Neural Network.<\/p>\n
<\/p>\n
\r\n\r\n#stargazer(traindt, type = \"text\", title=\"Descriptive statistics\", digits=1, out=\"table1.txt\")\r\n#write(summary(traindt), file=\"bnp-data-summary.txt\")\r\nsink(file=\"bnp-summary-stats.txt\")\r\nprint(str(bnpnet))\r\nprint(summary(bnpnet))\r\nprint(str(bnpnet))\r\nprint(summary(traindt))\r\nprint(str(testdt))\r\nprint(summary(testdt))\r\n\r\nsink()\r\n\r\n#simp1\r\n\r\n#nnet\r\n# bnpnet #bnpnet #bnpred #traindt #testdt #source('\/Users\/jarina\/Downloads\/bnp-sim\/write-summary-stats.R')\r\n\r\nbnpred <- predict(bnpnet, testdt[,c(-1,-23,-52)])\r\n\r\nbnpnet <- nnet(traindt$target ~ ., data=traindt[,c(-1,-2,-24,-58)], size=3, MaxNWts=10000000)\r\n\r\n\r\ntestdt <- read.csv('\/Users\/shirish\/Downloads\/bnp-sim\/train.csv', header = TRUE, sep = ',', fill = FALSE, colClasses = rep(\u2019character\u2019,135))\r\n\r\n#removing v22, v56 and v71\r\n\r\n<\/code>\r\n<\/pre>\n <\/p>\n
References<\/h2>\n
<\/p>\n
\n- http:\/\/tutorials.iq.harvard.edu\/R\/Rgraphics\/Rgraphics.html<\/a><\/li>\n
- https:\/\/www.datacamp.com\/community\/tutorials\/15-easy-solutions-data-frame-problems-r<\/a><\/li>\n<\/ul>\n
R programming example<\/p>\n
\n- http:\/\/heather.cs.ucdavis.edu\/~matloff\/R\/RProg.pdf<\/a><\/li>\n
- http:\/\/www.clemson.edu\/economics\/faculty\/wilson\/R-tutorial\/graphics.html<\/a><\/li>\n
- http:\/\/www.stat.berkeley.edu\/~s133\/saving.html<\/a><\/li>\n
- http:\/\/www.stat.auckland.ac.nz\/~paul\/RGraphics\/rgraphics.html<\/a><\/li>\n
- http:\/\/addictedtor.free.fr\/graphiques\/ http:\/\/addictedtor.free.fr\/graphiques\/thumbs.php?sort=votes<\/a><\/li>\n
- http:\/\/www.statmethods.net\/advgraphs\/layout.html<\/a><\/li>\n
- http:\/\/lattice.r-forge.r-project.org\/Vignettes\/src\/lattice-intro\/lattice-intro.pdf<\/a><\/li>\n
- http:\/\/www.cookbook-r.com\/Graphs\/Histogram_and_density_plot\/<\/a><\/li>\n
- http:\/\/www.cookbook-r.com<\/a><\/li>\n<\/ul>\n
Missing data<\/p>\n
\n- https:\/\/www3.nd.edu\/~rwilliam\/stats2\/l12.pdf<\/a><\/li>\n
- http:\/\/www.ats.ucla.edu\/stat\/sas\/library\/multipleimputation.pdf<\/a><\/li>\n
- https:\/\/cran.r-project.org\/web\/packages\/mi\/mi.pdf<\/a><\/li>\n
- https:\/\/cran.r-project.org\/web\/packages\/Amelia\/vignettes\/amelia.pdf<\/a><\/li>\n
- http:\/\/www.ats.ucla.edu\/stat\/sas\/library\/multipleimputation.pdf<\/a><\/li>\n
- http:\/\/www.stats.ox.ac.uk\/~matechou\/Principles\/MissingData.pdf<\/a>http:\/\/www.princeton.edu\/~otorres\/sessions\/s2r.pdf<\/a> (very good summary slides on r)<\/li>\n<\/ul>\n
Data stuff<\/p>\n
\n- http:\/\/www.gettinggeneticsdone.com\/2011\/02\/split-data-frame-into-testing-and.html<\/a><\/li>\n
- http:\/\/www.cookbook-r.com\/Manipulating_data\/Adding_and_removing_columns_from_a_data_frame\/<\/a><\/li>\n
- http:\/\/www.statmethods.net\/management\/subset.html<\/a><\/li>\n
- https:\/\/statnet.org\/trac\/raw-attachment\/wiki\/Resources\/introToSNAinR_sunbelt_2012_tutorial.pdf<\/a><\/li>\n<\/ul>\n
Network Analysis<\/p>\n
\n- http:\/\/sna.stanford.edu\/rlabs.php<\/a><\/li>\n
- http:\/\/www.insna.org<\/a><\/li>\n
- https:\/\/statnet.org\/trac\/raw-attachment\/wiki\/Resources\/introToSNAinR_sunbelt_2012_tutorial.pdf<\/a><\/li>\n
- https:\/\/www.calvin.edu\/~scofield\/courses\/m143\/materials\/RcmdsFromClass.pdf<\/a><\/li>\n
- http:\/\/statweb.stanford.edu\/~susan\/courses\/s141\/RNotes.pdf<\/a><\/li>\n
- http:\/\/www.inside-r.org\/packages\/cran\/igraph\/docs<\/a><\/li>\n
- http:\/\/igraph.org\/r\/doc\/plot.common.html<\/a><\/li>\n
- http:\/\/horicky.blogspot.com\/2012\/04\/basic-graph-analytics-using-igraph.html<\/a> (this is a good one on network analysis)<\/li>\n
- https:\/\/cran.r-project.org\/web\/packages\/NeuralNetTools\/NeuralNetTools.pdf<\/a><\/li>\n
- https:\/\/journal.r-project.org\/archive\/2010-1\/RJournal_2010-1_Guenther+Fritsch.pdf<\/a><\/li>\n
- http:\/\/www.analyticsvidhya.com\/blog\/2016\/01\/xgboost-algorithm-easy-steps\/<\/a><\/li>\n<\/ul>\n
R and NNET Reference:<\/p>\n
\n- https:\/\/github.com\/krishna7189\/Rcodeeasy\/blob\/master\/NEURAL%20NETWORKS-%20Detailed%20solved%20Classification%20example%20-%20Packages%20using%20%22NNET%22%20and%20%22NEURALNET%22%20in%20R<\/a><\/li>\n
- https:\/\/beckmw.wordpress.com\/tag\/nnet\/<\/a> (loos good)<\/li>\n
- http:\/\/www.di.fc.ul.pt\/~jpn\/r\/neuralnets\/neuralnets.html<\/a> (good compare with nnet, nueralnet, and NN with caret)<\/li>\n
- http:\/\/gekkoquant.com\/2012\/05\/26\/neural-networks-with-r-simple-example\/<\/a><\/li>\n
- http:\/\/horicky.blogspot.com\/2012\/06\/predictive-analytics-neuralnet-bayesian.html<\/a><\/li>\n<\/ul>\n
xgboot libraries<\/p>\n