tsa.test.UI | R Documentation |
Implimentation of Bowman and Somers (2006) Test Site Analysis (http://goo.gl/h4JAGP).
For implimenation as in Bowman and Somers (2006) use distance=NULL, outlier.rem=F, m.select=F. This function allows optional funcationality including automatic selection of
indicator metrics using metric.select
, as well as outlier removal from the reference set using arw
or pcout
.
An alternative mahalnobis distance calculation is also implimented using weighted means and covariance matrix. The weights are supplied from
the ecological distance between test sites and reference sites using site.match
.
tsa.test.UI(
Test,
Reference,
distance = NULL,
outlier.rem = F,
m.select = F,
rank = F,
na.cutoff = 0.7,
outbound = 0.1
)
Test |
Data frame of metric scores at the test site. |
Reference |
Data frame of metric scores at the reference sites. |
distance |
Vector of weights to use for optional weighted Mahalanobis Distance calculation. Can be output of |
outlier.rem |
Logical argument indicating whether |
m.select |
Logical argument indicating whether the best subset of metrics should be automatically selected from the data. |
na.cutoff |
A value between 0-1 indicating the percent of the reference set that can contain NAs for any metric. NAs are replaced by the mean value. |
outbound |
Used if outlier.rem=T A numeric value between 0 and 1 indicating the outlier boundary for defining values as final outliers (default to 0.1) |
$general.results - Table containing the number and names of reference sites used and number of indicator metrics used
$tsa.results - Table containing the status rank of the test site, numerical interval and equivalence test, test site's mahalanobis sistance, the upper and lower critical mahalanobis distance values, the non-centrallity parameter lambda and F-value of the test site
$jacknife - Table conataining the jacknifed consistency of the status rank and 95
$partial.tsa - Only present if the test site is ranked impaired or possibly impaired. Table containing p and F values for each metric's contribution to the overall mahalanobis distance score
$mahalanobis.distance - vector of reference sites and test site mahalanobis distance scores
$z.scores - Table containing test and reference sites metrics standrdized to z-scores of the reference sites only
#load datasets
data(YKEnvData,envir = environment()) #Biological dataset
data(YKBioData,envir = environment()) #Environmental dataset
#Calculate indicator metrics from raw biological data
bio.data.test<-benth.met(YKBioData,2,2)
#Extract just the summary metrics
bio.data<-bio.data.test$Summary.Metrics
#standardize row names between datasets
rownames(YKEnvData)<-bio.data.test$Site.List
#Match a test site (#201) to the nearest neighbour reference set
nn.sites<-site.match(YKEnvData[201,-c(1)],YKEnvData[1:118,-c(1)],k=NULL,adaptive=T)
#Calculate additional metrics based on selected Reference sites
taxa.data<-add.met(Test=bio.data.test$Raw.Data[201,],Reference=bio.data.test$Raw.Data[names(nn.sites$final.dist),])
#TSA test of indicator metrics at test site and reference sites selected used site.match()
tsa.results<-tsa.test(Test=taxa.data[nrow(taxa.data),],Reference=taxa.data[names(nn.sites$final.dist),],distance=nn.sites$final.dist, outlier.rem=T, m.select=T)
tsa.results
#Evaluate Results
boxplot(tsa.results)
plot(tsa.results)
pcoa.tsa(tsa.results)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.