The ade4 Package - NexTag Supports Open Source Initiatives

More documents

Recommendations

Info

162 mollusc References Mallat, S. G. (1989) A theory for multiresolution signal decomposition: the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, 7, 674–693. Percival, D. B. and Walden, A. T. (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press. See Also gridrowcol, orthobasis, orthogram, mra for multiresolution analysis with various families of wavelets Examples ## Not run: # decomposition of a time serie data(co2) x
monde84 163 Format <strong>Source</strong> mollusc is a list of 2 objects. fau is a data frame with 163 samples and 32 mollusk species (abundance). plan contains the 163 samples and 4 variables. Richardot-Coulet, M., Chessel D. and Bournaud M. (1986) Typological value of the benthos of old beds of a large river. Methodological approach. Archiv fùr Hydrobiologie, 107, 363–383. Examples data(mollusc) coa1
Page 1 and 2:
The ade4 Package February 16, 2008
Page 3 and 4:
R topics documented: 3 dudi.acm . .
Page 5 and 6:
R topics documented: 5 plot.phylog
Page 7 and 8:
EH 7 EH Amount of Evolutionary Hist
Page 9 and 10:
RV.rtest 9 RV.rtest Monte-Carlo Tes
Page 11 and 12:
acacia 11 Format abouheif.eg is a l
Page 13 and 14:
add.scatter 13 Usage add.scatter(fu
Page 15 and 16:
ade4toR 15 Arguments fictab ficcoln
Page 17 and 18:
amova 17 amova Analysis of molecula
Page 19 and 20:
ardeche 19 ardeche Fauna Table with
Page 21 and 22:
area.plot 21 Value possub cpoint la
Page 23 and 24:
arrival 23 # 4 fr.poly
Page 25 and 26:
atlas 25 par(mfrow = c(1,1)) all(di
Page 27 and 28:
avijons 27 Examples ## Not run: dat
Page 29 and 30:
avimedi 29 par(mfcol=c(3,2)) s.valu
Page 31 and 32:
acteria 31 Details aviurba$mil cont
Page 33 and 34:
aran95 33 eparlog : "Savings and lo
Page 35 and 36:
etween 35 par(mfrow = c(1,1)) betwe
Page 37 and 38:
icenter.wt 37 Format Source A list
Page 39 and 40:
setal97 39 Format bsetal97 is a lis
Page 41 and 42:
utterfly 41 Examples data(buech) pa
Page 43 and 44:
capitales 43 is.euclid(d1) # TRUE p
Page 45 and 46:
carniherbi49 45 Format Source carni
Page 47 and 48:
cca 47 Usage data(casitas) Format T
Page 49 and 50:
chatcat 49 s.match(iv1$ls, iv1$li,
Page 51 and 52:
chazeb 51 chazeb Charolais-Zebus De
Page 53 and 54:
cnc2003 53 Usage data(clementines)
Page 55 and 56:
coinertia 55 coinertia Coinertia An
Page 57 and 58:
coleo 57 coleo Table of Fuzzy Biolo
Page 59 and 60:
corvus 59 Examples data(friday87) f
Page 61 and 62:
disc 61 disc Rao’s dissimilarity
Page 63 and 64:
discrimin.coa 63 See Also lda in pa
Page 65 and 66:
dist.dudi 65 5 = Czekanowski (1913)
Page 67 and 68:
dist.genet 67 Let P the table of ge
Page 69 and 70:
dist.prop 69 Value returns a distan
Page 71 and 72:
dist.quant 71 Arguments df method d
Page 73 and 74:
divcmax 73 divcmax Maximal value of
Page 75 and 76:
dotchart.phylog 75 Usage dotchart.p
Page 77 and 78:
doubs 77 doubs Pair of Ecological T
Page 79 and 80:
dpcoa 79 Value option csize the fun
Page 81 and 82:
dudi.acm 81 Value as.dudi and all t
Page 83 and 84:
dudi.coa 83 Examples data(ours) sum
Page 85 and 86:
dudi.fca 85 Arguments df eff scannf
Page 87 and 88:
dudi.hillsmith 87 data(bsetal97) w
Page 89 and 90:
dudi.mix 89 Details If df contains
Page 91 and 92:
dudi.pca 91 dudi.pca Principal Comp
Page 93 and 94:
dudi.pco 93 Usage dudi.pco(d, row.w
Page 95 and 96:
ecg 95 ecg Electrocardiogram data D
Page 97 and 98:
elec88 97 References See a data des
Page 99 and 100:
escopage 99 escopage K-tables of wi
Page 101 and 102:
foucart 101 References Cheverud, J.
Page 103 and 104:
friday87 103 friday87 Faunistic K-t
Page 105 and 106:
fuzzygenet 105 fuzzygenet Reading a
Page 107 and 108:
genet 107 Value Returns an object o
Page 109 and 110:
genet 109 Value char2genet returns
Page 111 and 112: granulo 111 Examples if(require(pix
Page 113 and 114: hdpg 113 Examples w
Page 115 and 116: humDNAm 115 Usage data(housetasks)
Page 117 and 118: inertia.dudi 117 inertia.dudi Stati
Page 119 and 120: is.euclid 119 contour is a data fra
Page 121 and 122: julliot 121 Format julliot is a lis
Page 123 and 124: kcponds 123 Examples data(jv73) s.l
Page 125 and 126: kdist 125 Details The attributs of
Page 127 and 128: kdisteuclid 127 Value returns a lis
Page 129 and 130: kplot 129 kplot Generic Function fo
Page 131 and 132: kplot.mfa 131 csub possub a charact
Page 133 and 134: kplot.sepan 133 which.graph an opti
Page 135 and 136: kplot.statis 135 w
Page 137 and 138: ktab 137 Value plot.krandtest draws
Page 139 and 140: ktab.data.frame 139 Examples data(f
Page 141 and 142: ktab.list.dudi 141 Examples data(jv
Page 143 and 144: ktab.within 143 Examples data(meau)
Page 145 and 146: lingoes 145 Examples data(lascaux)
Page 147 and 148: macaca 147 References Bauwens, D.,
Page 149 and 150: mantel.randtest 149 Source Belair,
Page 151 and 152: maples 151 Arguments m1 m2 nrepet a
Page 153 and 154: mcoa 153 Source Codes for rows and
Page 155 and 156: meau 155 Examples data(friday87) w1
Page 157 and 158: mfa 157 mfa Multiple Factorial Anal
Page 159 and 160: microsatt 159 Format microsatt is a
Page 161: mld 161 Examples data(mjrochet) mjr
Page 165 and 166: 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 and 218:
andtest.amova 217 Examples par(mfro
Page 219 and 220:
andtest.coinertia 219 randtest.coin
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
Page 269 and 270:
score.mix 269 par(mfrow = c(1,1)) s
Page 271 and 272:
seconde 271 seconde Students and Su
Page 273 and 274:
skulls 273 skulls Morphometric Evol
Page 275 and 276:
steppe 275 C.T4 TL TC T4 a data fra
Page 277 and 278:
suprow 277 Details If supcol.defaul
Page 279 and 280:
symbols.phylog 279 symbols.phylog R
Page 281 and 282:
table.cont 281 Format Source t3012
Page 283 and 284:
table.paint 283 Usage table.dist(d,
Page 285 and 286:
table.value 285 labels.col clabel.c
Page 287 and 288:
tarentaise 287 Format tarentaise is
Page 289 and 290:
testdim 289 testdim Function to per
Page 291 and 292:
tithonia 291 s.label(tintoodiel$xy,
Page 293 and 294:
toxicity 293 points(ref,xyz[,2], pc
Page 295 and 296:
triangle.plot 295 show.position a l
Page 297 and 298:
trichometeo 297 Examples data (euro
Page 299 and 300:
uniquewt.df 299 Source Data were ob
Page 301 and 302:
vegtf 301 Value Returns a list cont
Page 303 and 304:
westafrica 303 Details The columns
Page 305 and 306:
within 305 afri.ms
Page 307 and 308:
withinpca 307 withinpca Normed with
Page 309 and 310:
worksurv 309 References Cazes, P.,
Page 311 and 312:
zealand 311 Examples data(yanomama)
Page 313 and 314:
Index ∗Topic array cailliez, 36 d
Page 315 and 316:
INDEX 315 krandtest, 130 randtest,
Page 317 and 318:
INDEX 317 bf88, 30 bicenter.wt, 31
Page 319 and 320:
INDEX 319 plot.procuste (procuste),
Page 321:
INDEX 321 wavelet.filter, 181 westa
show all

The ade4 Package - NexTag Supports Open Source Initiatives

Create successful ePaper yourself

Delete template?

Save as template?