Calculates the lasker kinship coeffcient

Share:

Description

“Lasker”calculates the lasker kinship coefficient starting from a surname frequency table.

Usage

1
lasker(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 subpopulations

Details

The use of “lasker” 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 “lasker” works.

Value

Returns a square symmetric kinship matrix.

Note

...

Author(s)

Federico C. F. Calboli and Alessio Boattini alessio.boattini2@unibo.it

References

Lasker, G.W. 1977. A coefficient of relationship by isonymy: A method for estimating the genetic relationship between populations. Hum. Biol. 49:489-493.

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, hedrickand uri for other types of inter-population kinship matrices

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
# 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
lask.kin <- lasker(tot)
lask.kin # a kinship matrix

#starting from a generic surname frequency table
data(surnames)
surnames #a made-up dataset
# the surnames are arranged as the _rows_ and the populations are the _columns_
# the use of the function ``Lasker'' just turns this data into a kinship matrix
lask.kin <- lasker(surnames)
lask.kin