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MARC Record from marc_columbia

Record ID marc_columbia/Columbia-extract-20221130-025.mrc:122038716:5871
Source marc_columbia
Download Link /show-records/marc_columbia/Columbia-extract-20221130-025.mrc:122038716:5871?format=raw

LEADER: 05871cam a22005174i 4500
001 12294537
005 20170117123838.0
008 110719s2011 caua 001 0 eng
010 $a 2011025598
020 $a9781593273842
020 $a1593273843
035 $a(OCoLC)ocn711045702
035 $a(OCoLC)711045702
035 $a(NNC)12294537
040 $aDLC$beng$erda$cDLC$dYDX$dBTCTA$dYDXCP$dOCO$dBWX$dCDX$dIG#$dBDX$dOUP$dOCLCF$dOCLCQ$dGBVCP$dOCLCQ$dS3O$dRB0$dMBU
042 $apcc
050 00 $aQA276.4$b.M2925 2011
060 4 $aQA 276.45 .R3 M2925a 2011
082 00 $a519.50285/5133$223
100 1 $aMatloff, Norman S.,$eauthor.
245 14 $aThe art of R programming :$ba tour of statistical software design /$cby Norman Matloff.
264 1 $aSan Francisco :$bNo Starch Press,$c[2011]
300 $axxiii, 373 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
500 $aIncludes index.
505 0 $aIntroduction -- Why use R for your statistical work? -- Whom is this book for? -- My own background -- Getting started -- How to run R -- A first R session -- Introduction to functions -- Preview of some important R data structures -- Extended example: regression analysis of exam grades -- Startup and shutdown -- Getting help -- Vectors -- Scalars, vectors, arrays, and matrices -- Declarations -- Recycling -- Common vector operations -- Using all() and any() -- Vectorized operations -- NA and NULL values -- Filtering -- A vectorized if-then-else: the ifelse() function -- Testing vector equality -- Vector element names -- More on c() -- Matrices and arrays -- Creating matrices -- General matrix operations -- Applying functions to matrix rows and columns -- Adding and deleting matrix rows and columns -- More on the vector/matrix distinction -- Avoiding unintended dimension reduction -- Naming matrix rows and columns -- Higher-dimensional arrays -- Lists -- Creating lists -- General list operations -- Accessing list components and values -- Applying functions to lists -- Recursive lists -- Data frames -- Creating data frames -- Other matrix-like operations -- Merging data frames -- Applying functions to data frames -- Factors and tables -- Factors and levels -- Common functions used with factors -- Working with tables -- Other factor and table-related functions -- R programming structures -- Control statements -- Arithmetic and Boolean operators and values -- Default values for arguments -- Return values -- Functions are objects -- Environment and scope issues -- No pointers in R -- Writing upstairs -- Recursion -- Replacement functions -- Tools for composing function code -- Writing your own binary operations -- Anonymous functions -- Doing math and simulations in R -- Math functions -- Functions for statistical distributions -- Sorting -- Linear algebra operations on vectors and matrices -- Set operations -- Simulation programming in R.
505 0 $aObject-oriented programming -- S3 classes -- S4 classes -- S3 versus S4 -- Managing your objects -- Input/output -- Accessing the keyboard and monitor -- Reading and writing files -- Accessing the Internet -- String manipulation -- An overview of string-manipulation functions -- Regular expressions -- Use of string utilities in the edtdbg debugging tool -- Graphics -- Creating graphs -- Customizing graphs -- Saving graphs to files -- Creating three-dimensional plots -- Debugging -- Fundamental principles of debugging -- Why use a debugging tool? -- Using R debugging facilities -- Moving up in the world: more convenient debugging tools -- Ensuring consistency in debugging simulation code -- Syntax and runtime errors -- Running GDB on R itself -- Performance enhancement: speed and memory -- Writing fast R code -- The dreaded for loop -- Functional programming and memory issues -- Using Rprof() to find slow spots in your code -- Byte code compilation -- Oh no, the data doesn't fit into memory! -- Interfacing R to other languages -- Writing C/C++ functions to be called from R -- Using R from Python -- Parallel R -- The mutual outlinks problem -- Introducing the snow package -- Resorting to C -- General performance considerations -- Debugging parallel R code -- Installing R -- Downloading R from CRAN -- Installing from a Linux package manager -- Installing from source -- Installing and using packages -- Package basics -- Loading a package from your hard drive -- Downloading a package from the Web -- Listing the functions in a package.
520 $aA guide to software development using the R programming language covers such topics as closures, recursion, anonymous functions, and debugging techniques.
650 0 $aStatistics$xData processing.
650 0 $aR (Computer program language)
650 7 $aR (Computer program language)$2fast$0(OCoLC)fst01086207
650 7 $aStatistics$xData processing.$2fast$0(OCoLC)fst01132113
650 7 $aR$2gnd$0(DE-601)356147487
650 7 $aStatistik$2gnd$0(DE-601)106152955
650 7 $aPubbz R.$2sao
650 7 $aStatistik - databehandling.$2sao
650 7 $aMatematisk statistik.$2sao
856 41 $3Table of contents$uhttp://catdir.loc.gov/catdir/enhancements/fy1205/2011025598-t.html
856 41 $3Table of contents$uhttp://catdir.loc.gov/catdir/enhancements/fy1201/2011025598-t.html
856 42 $3Contributor biographical information$uhttp://catdir.loc.gov/catdir/enhancements/fy1205/2011025598-b.html
856 42 $3Contributor biographical information$uhttp://catdir.loc.gov/catdir/enhancements/fy1114/2011025598-b.html
856 42 $3Publisher description$uhttp://catdir.loc.gov/catdir/enhancements/fy1205/2011025598-d.html
856 42 $3Publisher description$uhttp://catdir.loc.gov/catdir/enhancements/fy1114/2011025598-d.html
852 00 $boff,bus$hQA276.4$i.M2925 2011