mat.roc.allpair: ROC Analysis by Pairwise Comparisons

Description Usage Arguments Value Author(s) References See Also

View source: R/mat.roc.allpair.R

Description

Undertakes Receiver Operating Curve (ROC) analysis on a modern dataset when each row/site has a nominal class defining biological zone membership. This function undertakes ROC on a within-zone by out-zone basis. This function undertakes pairwise comparisons of zones.

Usage

1
mat.roc.allpair(inModern, modTaxa = c(), colClasses = NULL, numAnalogs = 2, rocEvalSeq = seq(0, 2, 0.05), counts = F, aucmethod = "trap")

Arguments

inModern

Dataframe: Modern Calibration Dataset: a file containing field names in the first row of the modern calibration dataset where each subsequent row containing a site/row identifier (Sample ID), coordinates in either a planar/projected x,y system or as Longitude and Latitude in decimal degrees, dd, and taxon counts followed by the modern environmental variables (Mod.Env 1,Mod.Env n) that will be used for modern training and/or paleoenvironmental reconstruction. The final and optional field would contain, for each row, a nominal code representing the biological zone to which each row/site belongs.

modTaxa

Vector: With two items, the number of the column containing the first taxon for analysis for each sample and the number of the column containing the last taxon for each sample within the inModern dataset.

colClasses

Numeric: The column of inModern that has the zonal affiliations for each sample.

numAnalogs

Numeric: a single number > 1 that specifies the number of modern analogs to use in the reconstruction.

rocEvalSeq

Vector: a numeric vector specifying the sequence over which the ROC analyses will be done. Generally, this sequence will range from the minimum value of the dissimilarity index to the maximum value of the dissimilarity index divided by some interval. For example, the default is set for squared-chord distance as rocEvalSeq=seq(0,2,0.05). This should be changed for other implementations of dissimilarity metrics.

counts

Logical: True (default) then the program assumes that your inFossil AND inModern datasets are taxon counts and so will automatically convert them to proportions.

aucmethod

Character: either "trap" for the trapezoidal integration or "wilcox" for the Mann-Whitney-Wilcoxon statistic.

Value

A LIST with the following components:

Zone1

ROC results for first zone

ZoneN

ROC results for last zone

Overall

ROC results for all zones lumped.

Author(s)

Dr. M. Sawada

References

SAWADA, M. 2006. An open-source implementation of the modern analog technique (MAT) within the R computing environment. Computers and Geosciences, Vol 32(6):818-833, DOI information: 10.1016/j.cageo.2005.10.008

See Also

mat.roc, mat.plotroc,mat.mc,


MATTOOLS documentation built on May 2, 2019, 2:11 a.m.