我正在尝试使用一个简单的数据集执行 RDA 分析，但即使数据是标准化的，我仍然遇到相同的错误。谁能帮我理解这个模型有什么问题？
`view(data_RDA)
summary(data_RDA)
abiotic.lake<-data_RDA[,c(1:11)]
biotic.lake<-data_RDA[,c(12:20)]
biotic.lake<-decostand(biotic.lake,"hellinger")
abiotic.lake<-decostand(abiotic.lake,"standardize")
rda.lake<- rda(biotic.lake,abiotic.lake)
plot(rda.lake,type="text") #The error starts at this point
anova.cca(rda.lake)
summary(rda.lake)
coef(rda.lake)
`
尝试运行情节线时出现的错误：
Error in cbind(x$CCA$v,x$CA$v)[,choices,drop = FALSE] :
subscript out of bounds
-
我认为没有执行分析，因为 rda.lake 的摘要仅返回 RDA1 结果。
-
数据被识别为数字。
-
anova.cca 函数仅返回零作为残差并且不显示 p 值，这让我相信数据或模型存在问题。
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这些是实际使用的表，都有 6 行。
生物湖
| Cian | Crip | 恐龙 | 克里斯 | Xant | 对话 | Eugl | Zigne | 克洛罗 |
|---|---|---|---|---|---|---|---|---|
| 0.0590634 | 0.21536114 | 1.286085 | 0.01117714 | 0.00000000 | 0.17741471 | 0.1438246 | 0.04127306 | 0.23323527 |
| 0.0590634 | 0.21536114 | 1.286085 | 0.01117714 | 0.00000000 | 0.17741471 | 0.1438246 | 0.04127306 | 0.23323527 |
| 0.0590634 | 0.21536114 | 1.286085 | 0.01117714 | 0.00000000 | 0.17741471 | 0.1438246 | 0.04127306 | 0.23323527 |
| 2.8144055 | 0.09724492 | 1.128178 | 0.02302370 | 0.03858338 | 0.01373549 | 0.9708160 | 0.90119103 | 0.08646308 |
| 2.8144055 | 0.09724492 | 1.128178 | 0.02302370 | 0.03858338 | 0.01373549 | 0.9708160 | 0.90119103 | 0.08646308 |
| 2.8144055 | 0.09724492 | 1.128178 | 0.02302370 | 0.03858338 | 0.01373549 | 0.9708160 | 0.90119103 | 0.08646308 |
非生物湖
| 教授 | Temp_H2O | OD | 条件 | N_Tot | NO2 | NO3 | SRP | SIO | Zmax | 宙斯 |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.0 | 20.7 | 8.15 | 98 | 230.72 | 9.28 | 294.32 | 15.91 | 3.72 | 4.8 | 4.5 |
| 2.0 | 20.4 | 7.16 | 105 | 228.61 | 8.56 | 352.34 | 8.92 | 4.49 | 4.8 | 4.5 |
| 4.8 | 20.0 | 5.20 | 107 | 190.82 | 6.82 | 293.81 | 11.15 | 7.82 | 4.8 | 4.5 |
| 0.0 | 30.4 | 9.24 | 100 | 610.28 | 3.46 | 42.82 | 36.15 | 13.17 | 5.0 | 2.0 |
| 2.0 | 28.3 | 6.62 | 110 | 612.11 | 3.63 | 48.19 | 32.19 | 11.94 | 5.0 | 2.0 |
| 5.0 | 25.8 | 2.13 | 115 | 560.31 | 4.69 | 60.98 | 35.30 | 11.03 | 5.0 | 2.0 |
- 编辑：根据需要，“dput”的输出
块引用
`dput(data_RDA)
structure(list(Prof = c(0,2,4.8,5),Temp_H2O = c(20.7,20.4,20,30.4,28.3,25.8),OD = c(8.15,7.16,5.2,9.24,6.62,2.13),Cond = c(98L,105L,107L,100L,110L,115L),N_Tot = c(230.72,228.61,190.82,610.28,612.11,560.31),NO2 = c(9.28,8.56,6.82,3.46,3.63,4.69),NO3 = c(294.32,352.34,293.81,42.82,48.19,60.98),SRP = c(15.91,8.92,11.15,36.15,32.19,35.3),SIO = c(3.72,4.49,7.82,13.17,11.94,11.03),Zmax = c(4.8,5,Zeu = c(4.5,4.5,2),Cian = c(0.0590634,0.0590634,2.814405487,2.814405487),Crip = c(0.215361139,0.215361139,0.097244921,0.097244921),Dino = c(1.286084811,1.286084811,1.128178481,1.128178481),Cris = c(0.011177144,0.011177144,0.023023705,0.023023705),Xant = c(1e-07,1e-07,0.038583378,0.038583378),Diat = c(0.17741471,0.17741471,0.01373549,0.01373549),Eugl = c(0.14382456,0.14382456,0.970816029,0.970816029),Zigne = c(0.041273061,0.041273061,0.901191033,0.901191033),Cloro = c(0.233235275,0.233235275,0.086463085,0.086463085)),class = "data.frame",row.names = c(NA,-6L))
- 编辑 2：根据需要，rda.lake 的输出：
块引用
'rda.lago
Call: rda(X = biotic.lake,Y = abiotic.lake)
Inertia Proportion Rank
Total 0.01198 1.00000
Constrained 0.01198 1.00000 1
Unconstrained 0.00000 0.00000 0
Inertia is variance
Some constraints were aliased because they were collinear (redundant)
Eigenvalues for constrained axes:
RDA1
0.011977 '
- 编辑 3：由 rda 分析生成的 NA。
块引用
'coef(rda.lake)
RDA1
Prof 0.003503013
Temp_H2O -0.152503172
OD 0.100134578
Cond 0.020938441
N_Tot -0.295691269
NO2 NA
NO3 NA
SRP NA
SIO NA
Zmax NA
Zeu NA '