| Record ID | marc_columbia/Columbia-extract-20221130-012.mrc:137940765:1955 |
| Source | marc_columbia |
| Download Link | /show-records/marc_columbia/Columbia-extract-20221130-012.mrc:137940765:1955?format=raw |
LEADER: 01955cam a22003614a 4500
001 5651383
005 20221121201058.0
008 051019s2006 flua b 001 0 eng
010 $a 2005054822
020 $a158488424X
024 3 $a9781584884248
035 $a(OCoLC)ocm62152943
035 $a(NNC)5651383
035 $a5651383
040 $aDLC$cDLC$dBAKER$dC#P$dIXA$dOrLoB-B
042 $apcc
050 00 $aQA279$b.F368 2006
082 00 $a519.5$222
100 1 $aFaraway, Julian James.$0http://id.loc.gov/authorities/names/n90696174
245 10 $aExtending the linear model with R :$bgeneralized linear, mixed effects and nonparametric regression models /$cJulian J. Faraway.
260 $aBoca Raton :$bChapman & Hall/CRC,$c2006.
300 $aix, 301 pages :$billustrations ;$c25 cm.
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
490 1 $aChapman & Hall/CRC texts in statistical science series
504 $aIncludes bibliographical references (p. 289-295) and index.
505 00 $g1.$tIntroduction -- $g2.$tBinomial data -- $g3.$tCount regression -- $g4.$tContingency tables -- $g5.$tMultinomial data -- $g6.$tGeneralized linear models -- $g7.$tOther GLMs -- $g8.$tRandom effects -- $g9.$tRepeated measures and longitudinal data -- $g10.$tMixed effect models for nonnormal responses -- $g11.$tNonparametric regression -- $g12.$tAdditive models -- $g13.$tTrees -- $g14.$tNeural networks -- $gA.$tLikelihood theory -- $gB.$tR information.
650 0 $aAnalysis of variance.$0http://id.loc.gov/authorities/subjects/sh85004782
650 0 $aRegression analysis.$0http://id.loc.gov/authorities/subjects/sh85112392
650 0 $aR (Computer program language)$xMathematical models.
830 0 $aTexts in statistical science.$0http://id.loc.gov/authorities/names/n94038042
856 42 $3Publisher description$uhttp://www.loc.gov/catdir/enhancements/fy0646/2005054822-d.html
852 00 $bmat$hQA279$i.F368 2006