Summary of tt_test() results.

# S3 method for tt_df
summary(object, ...)

# S3 method for tt_lst
summary(object, ...)

Arguments

object

An object of class "tt_df" or "tt_lst".

...

Not used (included only for compatibility with summary).

Value

A tibble.

See also

Author

Adapted from code contributed by Daniel Zuleta.

Examples

assert_is_installed("fgeo.x") tt_result <- tt_test(fgeo.x::tree6_3species, fgeo.x::habitat)
#> Using `plotdim = c(320, 500)`. To change this value see `?tt_test()`.
#> Using `gridsize = 20`. To change this value see `?tt_test()`.
summary(tt_result)
#> # A tibble: 12 x 3 #> sp habitat association #> <chr> <chr> <chr> #> 1 CASARB 1 neutral #> 2 CASARB 2 neutral #> 3 CASARB 3 neutral #> 4 CASARB 4 neutral #> 5 PREMON 1 neutral #> 6 PREMON 2 neutral #> 7 PREMON 3 neutral #> 8 PREMON 4 neutral #> 9 SLOBER 1 neutral #> 10 SLOBER 2 neutral #> 11 SLOBER 3 neutral #> 12 SLOBER 4 neutral
# Same summary(as_tibble(tt_result))
#> # A tibble: 12 x 3 #> sp habitat association #> <chr> <chr> <chr> #> 1 CASARB 1 neutral #> 2 CASARB 2 neutral #> 3 CASARB 3 neutral #> 4 CASARB 4 neutral #> 5 PREMON 1 neutral #> 6 PREMON 2 neutral #> 7 PREMON 3 neutral #> 8 PREMON 4 neutral #> 9 SLOBER 1 neutral #> 10 SLOBER 2 neutral #> 11 SLOBER 3 neutral #> 12 SLOBER 4 neutral
# You may want to add the explanation to the result of `tt_test()` dplyr::left_join(as_tibble(tt_result), summary(tt_result))
#> Joining, by = c("habitat", "sp")
#> # A tibble: 12 x 9 #> habitat sp N.Hab Gr.Hab Ls.Hab Eq.Hab Rep.Agg.Neut Obs.Quantile #> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1 CASA… 29 1242 356 2 0 0.776 #> 2 2 CASA… 20 390 1206 4 0 0.244 #> 3 3 CASA… 12 778 817 5 0 0.486 #> 4 4 CASA… 5 932 658 10 0 0.582 #> 5 1 PREM… 91 1093 504 3 0 0.683 #> 6 2 PREM… 89 1254 344 2 0 0.784 #> 7 3 PREM… 40 305 1292 3 0 0.191 #> 8 4 PREM… 14 270 1322 8 0 0.169 #> 9 1 SLOB… 18 273 1324 3 0 0.171 #> 10 2 SLOB… 24 810 788 2 0 0.506 #> 11 3 SLOB… 17 1155 440 5 0 0.722 #> 12 4 SLOB… 7 1292 303 5 0 0.808 #> # … with 1 more variable: association <chr>
# You may prefer a wide matrix Reduce(rbind, tt_result)
#> N.Hab.1 Gr.Hab.1 Ls.Hab.1 Eq.Hab.1 Rep.Agg.Neut.1 Obs.Quantile.1 N.Hab.2 #> CASARB 29 1242 356 2 0 0.776250 20 #> PREMON 91 1093 504 3 0 0.683125 89 #> SLOBER 18 273 1324 3 0 0.170625 24 #> Gr.Hab.2 Ls.Hab.2 Eq.Hab.2 Rep.Agg.Neut.2 Obs.Quantile.2 N.Hab.3 #> CASARB 390 1206 4 0 0.24375 12 #> PREMON 1254 344 2 0 0.78375 40 #> SLOBER 810 788 2 0 0.50625 17 #> Gr.Hab.3 Ls.Hab.3 Eq.Hab.3 Rep.Agg.Neut.3 Obs.Quantile.3 N.Hab.4 #> CASARB 778 817 5 0 0.486250 5 #> PREMON 305 1292 3 0 0.190625 14 #> SLOBER 1155 440 5 0 0.721875 7 #> Gr.Hab.4 Ls.Hab.4 Eq.Hab.4 Rep.Agg.Neut.4 Obs.Quantile.4 #> CASARB 932 658 10 0 0.58250 #> PREMON 270 1322 8 0 0.16875 #> SLOBER 1292 303 5 0 0.80750
# You may prefer a wide dataframe tidyr::spread(summary(tt_result), "habitat", "association")
#> # A tibble: 3 x 5 #> sp `1` `2` `3` `4` #> <chr> <chr> <chr> <chr> <chr> #> 1 CASARB neutral neutral neutral neutral #> 2 PREMON neutral neutral neutral neutral #> 3 SLOBER neutral neutral neutral neutral