I think may be the functions svm() and procomp() and tree() for classification and clustering data are useful for your project.

Hi Diego,

Seems like you approach is ok. The problem is that u have points with same lat and long. Before use DelaunayTriangulation perform an aggregation in your dataset based on lat and long and its should work.

Hi Moreno,

How do I perform an aggregation on my dataset based on latitude and longitude?

Hi Diego could u provide the output of head(data) of your data here? So I can help u to figure out how to aggregate it.

head(dataset):

CLASS FAMILY SPECIES BS LTS LATITUDE

1 Allomalorhagida Pycnophyidae Cristaphyes abyssorum 8.66 28.3 47

2 Allomalorhagida Pycnophyidae Cristaphyes abyssorum 8.66 28.3 47

3 Allomalorhagida Pycnophyidae Cristaphyes abyssorum 8.66 28.3 41

4 Allomalorhagida Pycnophyidae Cristaphyes anomalus 8.69 NA -41

5 Allomalorhagida Pycnophyidae Cristaphyes anomalus 8.69 NA -44

6 Allomalorhagida Pycnophyidae Cristaphyes anomalus 8.69 NA -46

LONGITUDE DEPTH OCEAN

1 155 5766 W Pac

2 155 4980 W Pac

3 150 5250 W Pac

4 -72 35 E Pac

5 -74 35 E Pac

6 -57 NA W Atl

Once I apply the following:

coordinates(dataset)

So the easiest way to do it is:

require(dplyr)

dataset %

group_by(SPECIES, LONGITUDE, LATITUDE, OCEAN) %>%

summarize(N = n())

then

coordinates(dataset)

Thank you for your answer. However, I'm still receiving this error:

Error in rgeos::gDelaunayTriangulation(dataset) :

duplicate points not permitted

Even after performing the aggregation of my dataset in the way you suggested with dplyr. Where could be the mistake?

Hi Diego,

Sorry my bad I forgot about the fact the two different species could occur in a same point.

Try this approach

require(dplyr)

require(reshape2)

species_data %

select(LONGITUDE, LATITUDE, SPECIES )

species_data %

summarise_all(.,mean(., na.rm = TRUE))

data

Hi Moreno,

Thank you. Which is the meaning of the following function:

summarise_all(.,sum(.))?

It gets me the error "Error in tbl_vars(x) : object '.' not found", but I cannot figure out the function of this line.

This part sum all other variable in your data.

Try substitute it by

summarise_all(sum)