mat.jump: Optimize the alpha value
In MATTOOLS: Modern Calibration Functions for the Modern Analog Technique (MAT)

Description Usage Arguments Details Value Author(s) References See Also

The MATTOOLS function mat.jump optimizes the value of for a given number of analogs and modern dataset.

1	mat.jump(dObj, inModern, envColumn, cutoff = 0, calib = T)

`dObj`	List: A Dissimilarity Object from the mat.dissim function.
`inModern`	Dataframe: The modern dataset with column(s) representing environmental values at each modern sample site.
`envColumn`	Numeric: The number of the column with the environmental values to be reconstructed.
`cutoff`	Numeric: The critical value of dissimilarity based on a priori knowledge or determined via mat.roc or mat.mc functions
`calib`	Logical: T for modern calibration (default). If F then it is assumed that a set of fossil assemblages are being tested.

With a cutoff > 0, only pairwise complete observations are used.

A LIST with the following components:

`alpha`	Numeric: optimal alpha value.
`alphacor`	Datatable: two columns, alpha and correlation.

...

Professor Michael Sawada

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

mat.jumprecon, mat.plotjump,mat.dissim,

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