rri {Biodem}

Calculates an unbiased estimate of Regional Random Isonymy

Description

"rri" calculates an unbiased estimate of Regional Random Isonymy starting from surname frequencies.

Usage

rri(x)

Arguments

x

is a surname frequency table where the N rows correspond to the surnames present in the whole population and the M columns are the (sub)populations

Details

The function implements Morton's isonymy method as outlined by Relethford. Unbiased estimate of Regional Random Isonymy refers to random isonymy of the contemporary region relative to the founding population. This value is an argument needed to calculate 'a priori' and conditional kinship matrices using the "rel.phi" and "rel.cond" functions.

Value

Returns one numeric value.

Note

The use of “rri” could be problematic, because different people are likely to arrange isonymy data in different ways on their computers. We decided for a matrix format for the isonymy data; the function would originally accept data in a different format and then convert it internally, but this would be a problem for people with data arranged in a different format. In the end we decided to write a specific function, "sur.freq", to generate surname frequency tables directly from raw marriage data or marriage-like data (the most commonly used sources in bio-demographic studies). For other types of surname data, see the verbose explanation in the info for the dataset "surnames" so it would be clear for the user how “rri” works.

Author(s)

Federico C. F. Calboli and Alessio Boattini [e-mail]

References

Morton, N. E. 1973. Kinship bioassy. In: Genetic distance, J. F Crow and C Denniston (eds.). New York, Plenum Press, 97-104. Relethford, J. H. 1988. Estimation of kinship and genetic distance from surnames. Human Biology, 60(3): 475-492.

See Also

sur.freq to generate the input surname frequency table from marriage data, surnames for an explanation on how to generate the correct input table from other surname sources, uri to calculate an Unbiased Random Isonymy matrix, rel.phi to calculate an 'a priori' kinship matrix from isonymy data, rel.cond to calculate a conditional kinship matrix from isonymy data

Examples

# starting from a raw marriage records dataset:
data(valley)
tot <- sur.freq(valley,valley$PAR,valley$SURM,valley$SURF)
tot # a frequency table calculated above all the surnames
reg <- rri(tot)
reg # an unbiased estimate or Regional Random Isonymy

#starting from a generic surname frequency table
data(surnames)
surnames # a made-up dataset
# you can see that the surnames are arranged as the _rows_
# and the populations are the _columns_
reg <- rri(surnames)
reg # an unbiased estimate or Regional Random Isonymy