Spider Data — spider • mvpart

Data set on abundances of spiders and environmental predictors. All variables are rated on a 0-9 scale.

Usage

data(spider)

Format

A data frame with 28 observations with 12 species and 6 environmental predictors.

Source

Van der Aart, P. J. and N. Smeeck-Enserink. 1975. Correlations between distributions of hunting spiders (Lycosidae, Ctenidae) and environmental characteristics in a dune area. Netherlands Journal of Zoology. 25:1-45.

These data were analysed using multivariate trees in De'ath, G. 2002. Multivariate Regression Trees: A New Technique for Modelling Species-Environment Relationships. Ecology. 83(4):1103-1117

Examples

data(spider)
fit<-mvpart(as.matrix(spider[,1:12])~water+twigs+reft+herbs+moss+sand,spider)

summary(fit)
#> Call:
#> mvpart(form = as.matrix(spider[, 1:12]) ~ water + twigs + reft + 
#>     herbs + moss + sand, data = spider)
#>   n= 28 
#> 
#>           CP nsplit rel error    xerror       xstd
#> 1 0.51864091      0 1.0000000 1.1024522 0.12785880
#> 2 0.14489010      1 0.4813591 0.5611124 0.07291997
#> 3 0.07537481      2 0.3364690 0.4291382 0.07140515
#> 
#> Node number 1: 28 observations,    complexity param=0.5186409
#>   Means=0.3571,1.179,1.536,1.964,2.5,1.179,4.5,1.393,2.5,1.5,0.9286,0.4286, Summed MSE=50.64158 
#>   left son=2 (20 obs) right son=3 (8 obs)
#>   Primary splits:
#>       herbs < 8.5 to the left,  improve=0.5186409, (0 missing)
#>       water < 5.5 to the left,  improve=0.3015809, (0 missing)
#>       moss  < 6   to the right, improve=0.2483042, (0 missing)
#>       reft  < 7.5 to the right, improve=0.2123679, (0 missing)
#>       sand  < 5.5 to the right, improve=0.2008664, (0 missing)
#> 
#> Node number 2: 20 observations,    complexity param=0.1448901
#>   Means=0.1,1.3,0.75,0.6,0.5,0.3,2.9,0.8,2.1,1.5,1.2,0.6, Summed MSE=25.7775 
#>   left son=4 (11 obs) right son=5 (9 obs)
#>   Primary splits:
#>       water < 5.5 to the left,  improve=0.3985045, (0 missing)
#>       twigs < 3.5 to the left,  improve=0.3985045, (0 missing)
#>       reft  < 3.5 to the right, improve=0.3985045, (0 missing)
#>       moss  < 6   to the right, improve=0.3518347, (0 missing)
#>       herbs < 6.5 to the left,  improve=0.2054174, (0 missing)
#> 
#> Node number 3: 8 observations
#>   Means=1,0.875,3.5,5.375,7.5,3.375,8.5,2.875,3.5,1.5,0.25,0, Summed MSE=20.875 
#> 
#> Node number 4: 11 observations
#>   Means=0,0.1818,0.1818,0.3636,0.3636,0.1818,1.364,0.5455,3.364,2.727,2.182,1.091, Summed MSE=17.68595 
#> 
#> Node number 5: 9 observations
#>   Means=0.2222,2.667,1.444,0.8889,0.6667,0.4444,4.778,1.111,0.5556,0,0,0, Summed MSE=12.83951 
#>