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AnneChao / SpadeR

SpadeR provides simple R functions to compute various biodiversity indices and related (dis)similarity measures based on individual-based (abundance) data or sampling-unit-based (incidence) data taken from one or multiple communities/assemblages.
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Help with SimilarityMult: likely user error, not code issue. Error in rmultinom(nboot, sum(X2), p[, 2]) : NA in probability vector #12

Open thomatostew opened 4 years ago

thomatostew commented 4 years ago

I'm trying to obtain diversity indices/estimators and dissimilarity measures for a community abundance matrix comprised of samples taken from multiple assemblages. Specifically, I'm running Anne Chao's function:

SimilarityMult (estimating various similarity indices among N communities). Both richness and abundance-based N-community similarity indices are included" --Anne Chao's SpadeR package.

I use packages:

library(devtools)
install_github('AnneChao/SpadeR')
library(SpadeR)
library(vegan)

ISSUE

My community abundance matrix set-up: 108 species in rows, 144 sites/samples in columns.

I run:

SimilarityMult(bugs,"abundance",q=1,nboot=200,"relative")

which yields:

ERROR CODE "Error in rmultinom(nboot, sum(X2), p[, 2]) : NA in probability vector

I run:

SimilarityMult(bugs,"abundance",q=2,nboot=200,"relative")

which yields:

ERROR CODE "Error in rmultinom(1, ni[k], p[, k]) : NA in probability vector

Below I provide the information from which my data matrix can be recreated and used to run problematic code to find sources of error. I share a subset of my data which includes the first 20 rows and first 25 columns.

I run:

dput(bugs[1:20,c(1:25)])

Output:

bugs  <-  structure(list(V1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 8L, 0L, 0L, 12L, 0L, 0L, 0L), V2 = c(0L, 0L, 0L, 
7L, 0L, 1L, 0L, 5L, 0L, 0L, 0L, 0L, 2L, 235L, 0L, 0L, 453L, 8L, 
0L, 0L), V3 = c(0L, 0L, 0L, 13L, 0L, 0L, 0L, 2L, 2L, 0L, 0L, 
1L, 0L, 82L, 0L, 0L, 60L, 1L, 8L, 0L), V4 = c(0L, 0L, 0L, 4L, 
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1051L, 0L, 0L, 48L, 58L, 
0L, 0L), V5 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 47L, 0L, 0L, 5L, 3L, 0L, 0L), V6 = c(0L, 0L, 0L, 18L, 0L, 
3L, 0L, 7L, 5L, 0L, 0L, 3L, 1L, 271L, 0L, 0L, 176L, 21L, 0L, 
0L), V7 = c(0L, 1L, 0L, 16L, 0L, 21L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 2L, 0L, 0L, 35L, 0L, 0L, 0L), V8 = c(0L, 0L, 0L, 17L, 1L, 
1L, 0L, 2L, 3L, 0L, 0L, 0L, 0L, 52L, 0L, 1L, 28L, 32L, 0L, 0L
), V9 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
29L, 0L, 0L, 8L, 3L, 8L, 0L), V10 = c(0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 2L, 0L, 25L, 0L, 0L, 14L, 0L, 0L, 0L), V11 = c(0L, 
12L, 0L, 14L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 61L, 0L, 0L, 
32L, 0L, 6L, 0L), V12 = c(0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 152L, 0L, 0L, 8L, 3L, 0L, 0L), V13 = c(0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 15L, 
0L, 0L, 0L), V14 = c(0L, 0L, 0L, 14L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 67L, 0L, 0L, 23L, 10L, 0L, 0L), V15 = c(0L, 2L, 0L, 
5L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 2L, 1L, 0L, 1L, 2L, 4L, 
0L), V16 = c(0L, 0L, 1L, 10L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
0L, 30L, 0L, 0L, 2L, 18L, 0L, 0L), V17 = c(0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 3L, 2L, 2L, 0L), 
    V18 = c(0L, 0L, 0L, 1L, 0L, 1L, 0L, 4L, 0L, 0L, 0L, 0L, 0L, 
    14L, 0L, 0L, 37L, 10L, 0L, 0L), V19 = c(0L, 1L, 0L, 13L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 10L, 0L, 0L, 14L, 26L, 
    0L, 0L), V20 = c(0L, 0L, 0L, 6L, 0L, 2L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 18L, 0L, 0L, 2L, 12L, 0L, 0L), V21 = c(0L, 0L, 
    0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 0L, 0L, 0L, 41L, 0L, 0L, 
    13L, 0L, 0L, 0L), V22 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 101L, 0L, 0L, 15L, 5L, 0L, 0L), V23 = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 15L, 0L, 
    0L, 17L, 0L, 1L, 0L), V24 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 0L, 2L, 0L, 0L), V25 = c(0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 7L, 0L, 0L, 0L, 0L, 134L, 0L, 
    0L, 19L, 0L, 0L, 0L)), row.names = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17", "18", "19", "20"), class = "data.frame")

Produce dataframe

bugs

Input dataframe 'bugs' into SimilarityMult functions above.

I do not understand why the code fails. What can I do to make the function work properly? Any solution/advice on the matter would be greatly appreciated.

Thank you!

nohemihuanca commented 4 years ago

I am also having the same issue but in my case SimilarityMult(data,"abundance",q=1,nboot=200,"relative") # runs good SimilarityMult(bugs,"abundance",q=0,nboot=200,"relative") # give the same error as above ERROR CODE "Error in rmultinom(1, ni[k], p[, k]) : NA in probability vector