Distance Matrices
yanomama.Rd
This data set gives 3 matrices about geographical, genetic and anthropometric distances.
Usage
data(yanomama)
Format
yanomama
is a list of 3 components:
- geo
is a matrix of 19-19 geographical distances
- gen
is a matrix of 19-19 SFA (genetic) distances
- ant
is a matrix of 19-19 anthropometric distances
Source
Spielman, R.S. (1973) Differences among Yanomama Indian villages: do the patterns of allele frequencies, anthropometrics and map locations correspond? American Journal of Physical Anthropology, 39, 461--480.
References
Table 7.2 Distance matrices for 19 villages of Yanomama Indians. All distances are as given by Spielman (1973), multiplied by 100 for convenience in: Manly, B.F.J. (1991) Randomization and Monte Carlo methods in biology Chapman and Hall, London, 1--281.
Examples
data(yanomama)
gen <- quasieuclid(as.dist(yanomama$gen)) # depends of mva
ant <- quasieuclid(as.dist(yanomama$ant)) # depends of mva
par(mfrow = c(2,2))
plot(gen, ant)
t1 <- mantel.randtest(gen, ant, 99);
plot(t1, main = "gen-ant-mantel") ; print(t1)
#> Monte-Carlo test
#> Call: mantel.randtest(m1 = gen, m2 = ant, nrepet = 99)
#>
#> Observation: 0.2999879
#>
#> Based on 99 replicates
#> Simulated p-value: 0.04
#> Alternative hypothesis: greater
#>
#> Std.Obs Expectation Variance
#> 1.98608496 -0.01307343 0.02484639
t1 <- procuste.rtest(pcoscaled(gen), pcoscaled(ant), 99)
plot(t1, main = "gen-ant-procuste") ; print(t1)
#> Monte-Carlo test
#> Call: procuste.rtest(df1 = pcoscaled(gen), df2 = pcoscaled(ant), nrepet = 99)
#>
#> Observation: 0.6819023
#>
#> Based on 99 replicates
#> Simulated p-value: 0.01
#> Alternative hypothesis: greater
#>
#> Std.Obs Expectation Variance
#> 3.268216127 0.543003495 0.001806241
t1 <- RV.rtest(pcoscaled(gen), pcoscaled(ant), 99)
plot(t1, main = "gen-ant-RV") ; print(t1)
#> Monte-Carlo test
#> Call: RV.rtest(df1 = pcoscaled(gen), df2 = pcoscaled(ant), nrepet = 99)
#>
#> Observation: 0.4272698
#>
#> Based on 99 replicates
#> Simulated p-value: 0.02
#> Alternative hypothesis: greater
#>
#> Std.Obs Expectation Variance
#> 2.782273928 0.249075125 0.004101943