[R] 3 dimensional MDS plots

Sarah Goslee
2011-03-10T22:03:03Z

Hi Calla,

On Thu, Mar 10, 2011 at 3:38 PM, Calla Carbone <6cc4 at queensu.ca>
wrote:
> Hi,
>
> I am trying to create 3 mds plots: one with axis 1 vs axis 2, one with axis
2 vs axis 3, and one with axis 1 vs axis 3. When inputting my code, I only end
up with one diagram and when inputting
> mdsg.mds$dims, the program returns 2 for 2 dimensions. How can I create the
other two plots?
>

Assuming you are using metaMDS from the vegan package (it's important
to specify what package
you are using if your function is not in base R), the default option
is to use 2 dimensions. Since you
don't specify k, you only get 2 dimensions.

For NMDS, unlike most other ordination methods, you  need to choose
the number of dimensions
*first*.

mdsg.mds<- metaMDS(mdsg, k=3)

Sarah

> Any help would be greatly appreciated,
> Calla Carbone
>
>
> The table I use is number of each taxa on each surface and is attached.
>
>
>
>
> Below is a copy of my work:
>
>>mdsg=read.csv(file.choose(), header=TRUE, row.names=1,
sep=",")
>> mdsg.mds<- metaMDS(sp.rich)
> Error in metaMDS(sp.rich) : object 'sp.rich' not found
>> mdsg.mds<- metaMDS(mdsg)
> Square root transformation
> Wisconsin double standardization
> Run 0 stress 10.62813
> Run 1 stress 14.73774
> Run 2 stress 11.19939
> Run 3 stress 10.61520
> ... New best solution
> ... procrustes: rmse 0.005646588 ?max resid 0.009332332
> Run 4 stress 10.61520
> ... New best solution
> ... procrustes: rmse 0.0001009763 ?max resid 0.0001754211
> *** Solution reached
>
>> mdsg.mds.ALT<- metaMDS(mdsg, distance="euclidean", k=3,
trymax=50, autotransform=FALSE)
> Run 0 stress 3.020817
> Run 1 stress 0.00673153
> ... New best solution
> ... procrustes: rmse 0.09349157 ?max resid 0.2443702
> Run 2 stress 0.008861757
> ... procrustes: rmse 0.08275172 ?max resid 0.1932439
> Run 3 stress 0.006908548
> ... procrustes: rmse 0.0447681 ?max resid 0.1093436
> Run 4 stress 0.007621072
> ... procrustes: rmse 0.05445531 ?max resid 0.1437309
> Run 5 stress 0.005675308
> ... New best solution
> ... procrustes: rmse 0.1021018 ?max resid 0.2694876
> Run 6 stress 0.008473566
> ... procrustes: rmse 0.1411485 ?max resid 0.3583789
> Run 7 stress 0.008235768
> ... procrustes: rmse 0.05178896 ?max resid 0.1487678
> Run 8 stress 0.009192125
> ... procrustes: rmse 0.1135218 ?max resid 0.3126878
> Run 9 stress 0.00984179
> ... procrustes: rmse 0.1117180 ?max resid 0.3110542
> Run 10 stress 0.00942402
> ... procrustes: rmse 0.08053243 ?max resid 0.2261970
> Run 11 stress 0.008956116
> ... procrustes: rmse 0.06461741 ?max resid 0.1729917
> Run 12 stress 0.00871519
> ... procrustes: rmse 0.08382491 ?max resid 0.2297745
> Run 13 stress 0.006883284
> ... procrustes: rmse 0.05259355 ?max resid 0.1339228
> Run 14 stress 0.007745699
> ... procrustes: rmse 0.1032920 ?max resid 0.2410554
> Run 15 stress 0.009062592
> ... procrustes: rmse 0.07324642 ?max resid 0.2127011
> Run 16 stress 0.006311344
> ... procrustes: rmse 0.1242246 ?max resid 0.3201084
> Run 17 stress 0.00679012
> ... procrustes: rmse 0.05894517 ?max resid 0.1699838
> Run 18 stress 0.00892886
> ... procrustes: rmse 0.0886889 ?max resid 0.2505874
> Run 19 stress 0.007831356
> ... procrustes: rmse 0.04815574 ?max resid 0.1443481
> Run 20 stress 0.008307666
> ... procrustes: rmse 0.08109922 ?max resid 0.2286835
> Run 21 stress 0.009738125
> ... procrustes: rmse 0.04494221 ?max resid 0.0853707
> Run 22 stress 0.006648893
> ... procrustes: rmse 0.0714659 ?max resid 0.180198
> Run 23 stress 0.008319666
> ... procrustes: rmse 0.1326991 ?max resid 0.3451491
> Run 24 stress 0.007369039
> ... procrustes: rmse 0.1406218 ?max resid 0.3560638
> Run 25 stress 0.006693668
> ... procrustes: rmse 0.06047182 ?max resid 0.1445884
> Run 26 stress 0.007021456
> ... procrustes: rmse 0.06223025 ?max resid 0.1552082
> Run 27 stress 0.008450277
> ... procrustes: rmse 0.06290812 ?max resid 0.1474387
> Run 28 stress 0.007949867
> ... procrustes: rmse 0.06185912 ?max resid 0.1779437
> Run 29 stress 0.007607591
> ... procrustes: rmse 0.0791691 ?max resid 0.2204299
> Run 30 stress 0.007450255
> ... procrustes: rmse 0.1027691 ?max resid 0.2798933
> Run 31 stress 0.006476469
> ... procrustes: rmse 0.02180973 ?max resid 0.04587615
> Run 32 stress 0.008423953
> ... procrustes: rmse 0.05009894 ?max resid 0.1326238
> Run 33 stress 0.009818617
> ... procrustes: rmse 0.1293366 ?max resid 0.3352202
> Run 34 stress 0.009782313
> ... procrustes: rmse 0.02056321 ?max resid 0.04534656
> Run 35 stress 0.007691246
> ... procrustes: rmse 0.06954554 ?max resid 0.1907627
> Run 36 stress 0.009071507
> ... procrustes: rmse 0.03511019 ?max resid 0.08272775
> Run 37 stress 0.00867032
> ... procrustes: rmse 0.03915756 ?max resid 0.08640346
> Run 38 stress 0.008109802
> ... procrustes: rmse 0.04896411 ?max resid 0.09568495
> Run 39 stress 0.0065526
> ... procrustes: rmse 0.07546078 ?max resid 0.1902766
> Run 40 stress 0.007617851
> ... procrustes: rmse 0.02149247 ?max resid 0.0493953
> Run 41 stress 0.007433552
> ... procrustes: rmse 0.03954261 ?max resid 0.07601604
> Run 42 stress 0.008697543
> ... procrustes: rmse 0.1110775 ?max resid 0.2855709
> Run 43 stress 0.006243913
> ... procrustes: rmse 0.0806811 ?max resid 0.2283781
> Run 44 stress 0.008474417
> ... procrustes: rmse 0.1519882 ?max resid 0.3552259
> Run 45 stress 0.0083211
> ... procrustes: rmse 0.0727077 ?max resid 0.1767035
> Run 46 stress 0.008051925
> ... procrustes: rmse 0.06954848 ?max resid 0.172751
> Run 47 stress 0.009271762
> ... procrustes: rmse 0.09332512 ?max resid 0.2182002
> Run 48 stress 0.009197149
> ... procrustes: rmse 0.104169 ?max resid 0.2856122
> Run 49 stress 0.00656145
> ... procrustes: rmse 0.04243012 ?max resid 0.1266379
> Run 50 stress 0.006636944
> ... procrustes: rmse 0.09853805 ?max resid 0.2584870
>> names(mdsg.mds)
> [1] "points" ? ?"dims" ? ? ?"stress" ?
?"data" ? ? ?"distance" ?"converged"
> [7] "tries" ? ? "species" ? "call"
>> mdsg.mds$points
> ? ? ? ? ? ? [,1] ? ? ? ?[,2]
> Disc ?-0.75970137 ?0.82615812
> Johns ?1.09698866 -0.42726075
> LBW ? -0.69603453 -0.21063881
> Spbay -0.11433730 -0.03734453
> BC ? ? 0.80952315 ?0.09556815
> D ? ? ?0.50518560 -0.24053747
> E ? ? ?0.22159986 ?0.04797842
> G ? ? -0.40841770 -0.27384498
> LMP ? ?0.23686884 ?1.23858885
> PC ? ?-0.87625155 -0.64825212
> SH ? ?-0.01542367 -0.37041488
> attr(,"centre")
> [1] TRUE
> attr(,"pc")
> [1] TRUE
> attr(,"halfchange")
> [1] TRUE
>> mdsg.mds$dims
> [1] 2
>> mdsg.mds$stress
> [1] 10.61520
>> mdsg.mds$data
> [1] "wisconsin(sqrt(mdsg))"
>> mdsg.mds$distance
> [1] "bray"
>> mdsg.mds$converged
> [1] TRUE
>> mdsg.mds$tries
> [1] 4
>> mdsg.mds$species
> ? ? ? ? ? ? ? ? ? ? ? ?[,1] ? ? ? ?[,2]
> Charnia ? ? ? ? ?-0.64803962 -0.25570377
> Charniodiscus ? ?-0.29435409 ?0.05427335
> Ivesheadia ? ? ? -0.31324619 -0.33485080
> Thectardis ? ? ? -0.90038964 -0.63829244
> Tree.Frond ? ? ? -0.52192114 -0.15500003
> Fractofusus ? ? ? 0.77371091 -0.11631453
> Bradgatia ? ? ? ?-0.04960810 -0.21083582
> Pectinifrons ? ? ?0.04014456 -0.32244681
> Aspidella ? ? ? ?-0.45120914 ?0.39904260
> Hapsidophylla ? ? 0.50383940 -0.17459408
> Heimalora ? ? ? ?-0.10441330 ?0.62593841
> Ostrich.Feather ? 0.28843372 ?1.46582729
> Feather.Duster ? ?0.01804479 -0.02227495
> Tulip.Frond ? ? ? 0.66742592 ?0.73062070
> Trepassia ? ? ? ? 0.28843372 ?1.46582729
> Beothukis ? ? ? ? 0.73931198 -0.08363615
> Primocandelabrum -0.92508363 ?0.97772972
> Hadryniscala ? ? -0.92508363 ?0.97772972
> Blackbrookia ? ? ?1.33579627 -0.50564841
> Frondophyllas ? ? 0.28843372 ?1.46582729
> Parviscopa ? ? ? -0.92508363 ?0.97772972
> attr(,"shrinkage")
> [1] 0.6744097 0.7139844
> attr(,"centre")
> [1] ?1.788934e-18 -3.794708e-19
> attr(,"old.wa")
> [1] FALSE
>> mdsg.mds$call
> metaMDS(comm = mdsg)
>> mds1.mds
>
> Call:
> metaMDS(comm = mds1)
>
> Nonmetric Multidimensional Scaling using isoMDS (MASS package)
>
> Data: ? ? wisconsin(sqrt(mds1))
> Distance: bray
>
> Dimensions: 2
> Stress: ? ? 9.804838
> Two convergent solutions found after 3 tries
> Scaling: centring, PC rotation, halfchange scaling
> Species: expanded scores based on ?wisconsin(sqrt(mds1))?
>
>> variableScores<- mds1.mds$species
>> sampleScores<- mds1.mds$points
>> plot(mds1.mds)
>> plot(mds1.mds, type="n")
>> text(mds1.mds, display=c("sites"), choices=c(1,2),
col="blue", cex=0.7)
>> points(mds1.mds, display=c("species"), choices=c(1,2), pch=3,
col="red")
>
>

--
Sarah Goslee