Dear R-users
I applied vegan's varpart function to partition the effects of
explanatory matrices. Adj. R square for the unique fraction [a] is
0.25. Does anyone know why the decomposition by hand using rda gives
me a different result for [a] (constrained proportion is 0.32)? I used
cbind() for the conditional fractions, but it should be similar to
condition()?
Thanks very much
Sibylle
> AZ_var<-varpart(AZ, OeAF, Acker, Gruen)
> plot(AZ_var)
>
> AZ_var
Partition of variation in RDA
Call: varpart(Y = AZ, X = OeAF, Acker, Gruen)
Explanatory tables:
X1: OeAF
X2: Acker
X3: Gruen
No. of explanatory tables: 3
Total variation (SS): 239101
Variance: 1811.4
No. of observations: 133
Partition table:
Df R.square Adj.R.square Testable
[a+d+f+g] = X1 29 0.55103 0.42463 TRUE
[b+d+e+g] = X2 11 0.12135 0.04147 TRUE
[c+e+f+g] = X3 9 0.23870 0.18300 TRUE
[a+b+d+e+f+g] = X1+X2 40 0.64676 0.49318 TRUE
[a+c+d+e+f+g] = X1+X3 38 0.59086 0.42546 TRUE
[b+c+d+e+f+g] = X2+X3 20 0.36936 0.25675 TRUE
[a+b+c+d+e+f+g] = All 49 0.69072 0.50813 TRUE
Individual fractions
[a] = X1 | X2+X3 29 0.25139 TRUE
[b] = X2 | X1+X3 11 0.08268 TRUE
[c] = X3 | X1+X2 9 0.01495 TRUE
[d] 0 -0.00893 FALSE
[e] 0 -0.01412 FALSE
[f] 0 0.20033 FALSE
[g] 0 -0.01816 FALSE
[h] = Residuals 0.49187 FALSE
Controlling 1 table X
[a+d] = X1 | X3 29 0.24246 TRUE
[a+f] = X1 | X2 29 0.45171 TRUE
[b+d] = X2 | X3 11 0.07375 TRUE
[b+e] = X2 | X1 11 0.06856 TRUE
[c+e] = X3 | X1 9 0.00083 TRUE
[c+f] = X3 | X2 9 0.21528 TRUE
---
Use function 'rda' to test significance of fractions of interest
> rda(AZ, OeAF, cbind(Acker, Gruen))
Call: rda(X = AZ, Y = OeAF, Z = cbind(Acker, Gruen))
Inertia Proportion Rank
Total 1811.3728 1.0000
Conditional 669.0542 0.3694 20
Constrained 582.0993 0.3214 4
Unconstrained 560.2193 0.3093 4
Inertia is variance
Eigenvalues for constrained axes:
RDA1 RDA2 RDA3 RDA4
570.343 8.310 1.833 1.614
Eigenvalues for unconstrained axes:
PC1 PC2 PC3 PC4
533.129 12.619 11.618 2.854
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