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218 randtest.between randtest.between Monte-Carlo Test on the between-groups inertia percentage (in C). Description Performs a Monte-Carlo test on the between-groups inertia percentage. Usage ## S3 method for class 'between': randtest(xtest, nrepet = 999, ...) Arguments xtest an object of class between nrepet the number of permutations ... further arguments passed to or from other methods Value a list of the class randtest Author(s) Jean Thioulouse 〈ade4-jt@biomserv.univ-lyon1.fr〉 References Romesburg, H. C. (1985) Exploring, confirming and randomization tests. Computers and Geosciences, 11, 19–37. Examples data(meaudret) pca1
andtest.coinertia 219 randtest.coinertia Monte-Carlo test on a Co-inertia analysis (in C). Description Performs a Monte-Carlo test on a Co-inertia analysis. Usage ## S3 method for class 'coinertia': randtest(xtest, nrepet = 999, fixed=0, ...) Arguments Value xtest nrepet fixed an object of class coinertia the number of permutations when non uniform row weights are used in the coinertia analysis, this parameter must be the number of the table that should be kept fixed in the permutations ... further arguments passed to or from other methods a list of the class randtest Note A testing procedure based on the total coinertia of the analysis is available by the function randtest.coinertia. The function allows to deal with various analyses for the two tables. The test is based on random permutations of the rows of the two tables. If the row weights are not uniform, mean and variances are recomputed for each permutation (PCA); for MCA, tables are recentred and column weights are recomputed. If weights are computed using the data contained in one table (e.g. COA), you must fix this table and permute only the rows of the other table. The case of decentred PCA (PCA where centers are entered by the user) is not yet implemented. If you want to use the testing procedure for this case, you must firstly center the table and then perform a non-centered PCA on the modified table. The case where one table is treated by hill-smith analysis (mix of quantitative and qualitative variables) will be soon implemented. Author(s) Jean Thioulouse 〈ade4-jt@biomserv.univ-lyon1.fr〉 modified by Stephane Dray 〈dray@biomserv.univlyon1.fr〉 References Dolédec, S. and Chessel, D. (1994) Co-inertia analysis: an alternative method for studying speciesenvironment relationships. Freshwater Biology, 31, 277–294.
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The ade4 Package February 16, 2008
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R topics documented: 3 dudi.acm . .
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R topics documented: 5 plot.phylog
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EH 7 EH Amount of Evolutionary Hist
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RV.rtest 9 RV.rtest Monte-Carlo Tes
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acacia 11 Format abouheif.eg is a l
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add.scatter 13 Usage add.scatter(fu
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ade4toR 15 Arguments fictab ficcoln
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amova 17 amova Analysis of molecula
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ardeche 19 ardeche Fauna Table with
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area.plot 21 Value possub cpoint la
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arrival 23 # 4 fr.poly
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atlas 25 par(mfrow = c(1,1)) all(di
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avijons 27 Examples ## Not run: dat
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avimedi 29 par(mfcol=c(3,2)) s.valu
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acteria 31 Details aviurba$mil cont
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aran95 33 eparlog : "Savings and lo
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etween 35 par(mfrow = c(1,1)) betwe
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icenter.wt 37 Format Source A list
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setal97 39 Format bsetal97 is a lis
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utterfly 41 Examples data(buech) pa
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capitales 43 is.euclid(d1) # TRUE p
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carniherbi49 45 Format Source carni
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cca 47 Usage data(casitas) Format T
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chatcat 49 s.match(iv1$ls, iv1$li,
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chazeb 51 chazeb Charolais-Zebus De
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cnc2003 53 Usage data(clementines)
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coinertia 55 coinertia Coinertia An
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coleo 57 coleo Table of Fuzzy Biolo
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corvus 59 Examples data(friday87) f
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disc 61 disc Rao’s dissimilarity
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discrimin.coa 63 See Also lda in pa
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dist.dudi 65 5 = Czekanowski (1913)
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dist.genet 67 Let P the table of ge
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dist.prop 69 Value returns a distan
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dist.quant 71 Arguments df method d
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divcmax 73 divcmax Maximal value of
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dotchart.phylog 75 Usage dotchart.p
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doubs 77 doubs Pair of Ecological T
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dpcoa 79 Value option csize the fun
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dudi.acm 81 Value as.dudi and all t
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dudi.coa 83 Examples data(ours) sum
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dudi.fca 85 Arguments df eff scannf
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dudi.hillsmith 87 data(bsetal97) w
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dudi.mix 89 Details If df contains
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dudi.pca 91 dudi.pca Principal Comp
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dudi.pco 93 Usage dudi.pco(d, row.w
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ecg 95 ecg Electrocardiogram data D
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elec88 97 References See a data des
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escopage 99 escopage K-tables of wi
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foucart 101 References Cheverud, J.
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friday87 103 friday87 Faunistic K-t
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fuzzygenet 105 fuzzygenet Reading a
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genet 107 Value Returns an object o
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genet 109 Value char2genet returns
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granulo 111 Examples if(require(pix
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hdpg 113 Examples w
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humDNAm 115 Usage data(housetasks)
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inertia.dudi 117 inertia.dudi Stati
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is.euclid 119 contour is a data fra
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julliot 121 Format julliot is a lis
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kcponds 123 Examples data(jv73) s.l
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kdist 125 Details The attributs of
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kdisteuclid 127 Value returns a lis
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kplot 129 kplot Generic Function fo
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kplot.mfa 131 csub possub a charact
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kplot.sepan 133 which.graph an opti
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kplot.statis 135 w
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ktab 137 Value plot.krandtest draws
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ktab.data.frame 139 Examples data(f
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ktab.list.dudi 141 Examples data(jv
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ktab.within 143 Examples data(meau)
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lingoes 145 Examples data(lascaux)
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macaca 147 References Bauwens, D.,
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mantel.randtest 149 Source Belair,
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maples 151 Arguments m1 m2 nrepet a
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mcoa 153 Source Codes for rows and
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meau 155 Examples data(friday87) w1
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mfa 157 mfa Multiple Factorial Anal
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microsatt 159 Format microsatt is a
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mld 161 Examples data(mjrochet) mjr
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monde84 163 Format Source mollusc i
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mstree 165 mstree Minimal Spanning
Page 167 and 168: multispati 167 Value Returns an obj
Page 169 and 170: multispati.randtest 169 w1.msm
Page 171 and 172: neig 171 Author(s) Daniel Chessel S
Page 173 and 174: neig 173 #hist(dist, nclass = 50) m
Page 175 and 176: newick2phylog 175 References Bauwen
Page 177 and 178: niche 177 w[19]
Page 179 and 180: njplot 179 Author(s) Daniel Chessel
Page 181 and 182: optimEH 181 Source Example 357 in:
Page 183 and 184: originality 183 Details Variables o
Page 185 and 186: orisaved 185 orisaved Maximal or mi
Page 187 and 188: orthobasis 187 Value All the functi
Page 189 and 190: orthogram 189 orthogram Orthonormal
Page 191 and 192: ours 191 Examples # a phylogenetic
Page 193 and 194: palm 193 palm Phylogenetic and quan
Page 195 and 196: pcaiv 195 pcaiv Principal component
Page 197 and 198: pcaivortho 197 Arguments dudi df sc
Page 199 and 200: perthi02 199 Author(s) Daniel Chess
Page 201 and 202: phylog 201 paths droot call Wmat Wd
Page 203 and 204: plot.phylog 203 f.phylog circle cle
Page 205 and 206: presid2002 205 ## Not run: # plot a
Page 207 and 208: procuste 207 Format procella is a l
Page 209 and 210: procuste.randtest 209 References Di
Page 211 and 212: pta 211 Arguments df1 df2 nrepet a
Page 213 and 214: quasieuclid 213 Author(s) Pierre Ba
Page 215 and 216: andtest-internal 215 References Nee
Page 217: andtest.amova 217 Examples par(mfro
Page 221 and 222: ankrock 221 # Df Pillai approx F nu
Page 223 and 224: hone 223 rhone Physico-Chemistry Da
Page 225 and 226: lq 225 nf RV eig lw cw tab li l1 co
Page 227 and 228: test 227 Examples ## Not run: data(
Page 229 and 230: test.discrimin 229 References Romes
Page 231 and 232: s.chull 231 addaxes cgrid sub csub
Page 233 and 234: s.class 233 Examples xy 0) coul 0
Page 235 and 236: s.corcircle 235 possub = "bottomrig
Page 237 and 238: s.distri 237 Value clabel cpoint pc
Page 239 and 240: s.image 239 Examples data(rpjdl) co
Page 241 and 242: s.kde2d 241 s.image(t3012$xy, scale
Page 243 and 244: s.label 243 Arguments Value dfxy xa
Page 245 and 246: s.logo 245 Value xax yax neig cneig
Page 247 and 248: s.multinom 247 Value cgrid a charac
Page 249 and 250: s.traject 249 Value Returns in a hi
Page 251 and 252: s.value 251 Examples rw
Page 253 and 254: santacatalina 253 par(mfrow = c(3,4
Page 255 and 256: scalewt 255 scalewt Centring and Sc
Page 257 and 258: scatter 257 Author(s) See Also Dani
Page 259 and 260: scatter.dudi 259 Arguments x xax ya
Page 261 and 262: scatter.fca 261 scatter.fca Plot of
Page 263 and 264: sco.distri 263 banque.acm
Page 265 and 266: score 265 Arguments score df fac cl
Page 267 and 268: score.coa 267 Arguments x xax which
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score.mix 269 par(mfrow = c(1,1)) s
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seconde 271 seconde Students and Su
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skulls 273 skulls Morphometric Evol
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steppe 275 C.T4 TL TC T4 a data fra
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suprow 277 Details If supcol.defaul
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symbols.phylog 279 symbols.phylog R
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table.cont 281 Format Source t3012
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table.paint 283 Usage table.dist(d,
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table.value 285 labels.col clabel.c
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tarentaise 287 Format tarentaise is
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testdim 289 testdim Function to per
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tithonia 291 s.label(tintoodiel$xy,
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toxicity 293 points(ref,xyz[,2], pc
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triangle.plot 295 show.position a l
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trichometeo 297 Examples data (euro
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uniquewt.df 299 Source Data were ob
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vegtf 301 Value Returns a list cont
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westafrica 303 Details The columns
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within 305 afri.ms
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withinpca 307 withinpca Normed with
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worksurv 309 References Cazes, P.,
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zealand 311 Examples data(yanomama)
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Index ∗Topic array cailliez, 36 d
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INDEX 315 krandtest, 130 randtest,
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INDEX 317 bf88, 30 bicenter.wt, 31
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INDEX 319 plot.procuste (procuste),
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INDEX 321 wavelet.filter, 181 westa
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