[R] function for cumulative occurrence of elements

[Tony Plate]

I'm not entirely sure what you want, but is it "9 5 3" for this data? (9 
"new" species occur at the first point, 5 "new" at the second, and 3 
"new" at the third).  If this is right, then to get "accumulation curve 
when random Points are considered", you can probably just index rows of 
dt appropriately.

 > dd <- read.table("clipboard", header=T)
 > dd[,1:3]
    Point        species frequency
1      7   American_elm         7
2      7          apple         2
3      7   black_cherry         8
4      7      black_oak         1
5      7    chokecherry         1
6      7         oak_sp         1
7      7 pignut_hickory         1
8      7      red_maple         1
9      7      white_oak         5
10     9   black_spruce         2
11     9    blue_spruce         2
12     9        missing        12
13     9  Norway_spruce         8
14     9   white_spruce         3
15    12          apple         2
16    12   black_cherry         1
17    12   black_locust         1
18    12   black_walnut         1
19    12          lilac         3
20    12        missing         2
 > # dt: table of which species occur at which "Points"
 > dt <- table(dd$Point, dd$species)
 > # doc: for each species, the index of the "Point" where
 > # it first occurs
 > doc <- apply(dt, 2, function(x) which(x==1)[1])
 > doc
   American_elm          apple   black_cherry   black_locust      black_oak
              1              1              1              3              1
   black_spruce   black_walnut    blue_spruce    chokecherry          lilac
              2              3              2              1              3
        missing  Norway_spruce         oak_sp pignut_hickory      red_maple
              2              2              1              1              1
      white_oak   white_spruce
              1              2
 > table(doc)
doc
1 2 3
9 5 3
 >

hope this helps,

Tony Plate

Steven K Friedman wrote:
> Hello, 
> 
> I have a data set with 9700 records, and 7 parameters. 
> 
> The data were collected for a survey of forest communities.  Sample plots 
> (1009) and species (139) are included in this data set. I need to determine 
> how species are accumulated as new plots are considered. Basically, I want 
> to develop a species area curve. 
> 
> I've included the first 20 records from the data set.  Point represents the 
> plot id. The other parameters are parts of the information statistic H'. 
> 
> Using "Table", I can construct a data set that lists the occurrence of a 
> species at any Point (it produces a binary 0/1 data table). From there it 
> get confusing, regarding the most efficient approach to determining the 
> addition of new and or repeated species occurrences. 
> 
> ptcount <-  table(sppoint.freq$species, sppoint.freq$Point) 
> 
>  From here I've played around with colSums to calculate the number of species 
> at each Point.  The difficulty is determining if a species is new or 
> repeated.  Also since there are 1009 points a function is needed to screen 
> every Point. 
> 
> Two goals are of interest: 1) the species accumulation curve, and 2) an 
> accumulation curve when random Points are considered. 
> 
> Any help would be greatly appreciated. 
> 
> Thank you
> Steve Friedman 
> 
> 
>  Point        species frequency point.list point.prop   log.prop 
> point.hprime
> 1      7   American elm         7         27 0.25925926 -1.3499267    
> 0.3499810
> 2      7          apple         2         27 0.07407407 -2.6026897    
> 0.1927918
> 3      7   black cherry         8         27 0.29629630 -1.2163953    
> 0.3604134
> 4      7      black oak         1         27 0.03703704 -3.2958369    
> 0.1220680
> 5      7    chokecherry         1         27 0.03703704 -3.2958369    
> 0.1220680
> 6      7         oak sp         1         27 0.03703704 -3.2958369    
> 0.1220680
> 7      7 pignut hickory         1         27 0.03703704 -3.2958369    
> 0.1220680
> 8      7      red maple         1         27 0.03703704 -3.2958369    
> 0.1220680
> 9      7      white oak         5         27 0.18518519 -1.6863990    
> 0.3122961
> 10     9   black spruce         2         27 0.07407407 -2.6026897    
> 0.1927918
> 11     9    blue spruce         2         27 0.07407407 -2.6026897    
> 0.1927918
> 12     9        missing        12         27 0.44444444 -0.8109302    
> 0.3604134
> 13     9  Norway spruce         8         27 0.29629630 -1.2163953    
> 0.3604134
> 14     9   white spruce         3         27 0.11111111 -2.1972246    
> 0.2441361
> 15    12          apple         2         27 0.07407407 -2.6026897    
> 0.1927918
> 16    12   black cherry         1         27 0.03703704 -3.2958369    
> 0.1220680
> 17    12   black locust         1         27 0.03703704 -3.2958369    
> 0.1220680
> 18    12   black walnut         1         27 0.03703704 -3.2958369    
> 0.1220680
> 19    12          lilac         3         27 0.11111111 -2.1972246    
> 0.2441361
> 20    12        missing         2         27 0.07407407 -2.6026897    
> 0.1927918
> 
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