CODEWITHSUNDEEP
rvegan
andschar
andschar

Reputation: 3973

vegan::ordiR2step() doesn't find best-fit model

The vegan package includes the ordiR2step() function for model building, which can be used to identify the most important variables using the R2 and the p-value as goodness of fit measures. However for the dataset I was recently working with the function doesn't provide the best-fit model.

# data
RIKZ <- read.table("http://www.uni-koblenz-landau.de/en/campus-landau/faculty7/environmental-sciences/landscape-ecology/Teaching/RIKZ_data/at_download/file", header = TRUE)

# data preparation
Species <- RIKZ[ ,2:5]
ExplVar <- RIKZ[ , 9:15]
Species_fin <- Species[ rowSums(Species) > 0, ]
ExplVar_fin <- ExplVar[ rowSums(Species) > 0, ]

# rda
RIKZ_rda <- rda(Species_fin ~ . , data = ExplVar_fin, scale = TRUE)

# stepwise model building: ordiR2step()
require(vegan)
step_both_R2 <- ordiR2step(rda(Species_fin ~ salinity, data = ExplVar_fin, scale = TRUE),
                       scope = formula(RIKZ_rda),
                       direction = "both", R2scope = TRUE, Pin = 0.05,
                       steps = 1000)

Why does ordiR2step() not add the variable exposure to the model, although it would increase the explained variance?

If R2scope is set FALSE and the p-value criterion is increased (Pin = 0.15) it adds the variable exposure corretly but throws the following error: 

Error in terms.formula(tmp, simplify = TRUE) : 
  invalid model formula in ExtractVars

If R2scope is set TRUE (Pi = 0.15) exposure is not added.

Note: This might seem more as a statistic question and therefore more suitable for CV. However I think the problem is rather technical and better off here on SO.

Upvotes: 2

Views: 554

Answers (1)

Jari Oksanen
Jari Oksanen

Reputation: 3682

Please read the ordiR2step documentation: it will tell you why exposure is not added to the model. The help page tells that ordiR2step has three stopping criteria. The second criterion is that "the adjusted R2 of the ‘scope’ is exceeded". This happens with exposure and therefore it was not added. This second criterion will be ignored if you set R2scope = FALSE (also documented). So the function works like documented.

Upvotes: 1

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