The estimation of the fitness function from two samples taken from a population
Tóm tắt
The fitness of animals subjected to natural selection can be defined as the probability of surviving selection for a given interval of time, or some convenient multiple of this probability. If the fitness of animals is related to some quantitative variableX (such as size) then this relationship is expressed mathematically in the fitness functionw(x) and this function can be estimated by comparing the distribution ofX in samples taken before and after selection. In this note five methods for estimating the fitness function on the basis of samples from a large population are discussed. They are compared on three previously published sets of data and as a result estimation according to weighted multiple regression is recommended.
Tài liệu tham khảo
Cavalli-Sforza, L. L. andW. F. Bodmer (1972)The gnetics of human populations. Freeman, San Francisco.
Cook, L. M. (1971)Coefficients of natural selection. Hutchinson, London.
Dixon, W. H. (1973)Biomedical computer programs. Univ. California Press, Berkeley.
Dowdeswell, W. H. (1961) Experimental studies on natural selection in the butterflyManiola jurtina.Heredity 16: 39–52.
Hagen, D. W. andL. G. Gilbertson (1973) Selective predation and the intensity of selection acting upon the lateral plates of Threespine sticklebacks.Heredity 30: 273–87.
Kendall, M. G. andA. Stuart (1963)The advanced theory of statistics, vol. 1. Griffin, London.
Kowalik, J. andM. R. Osborne (1968)Methods for unconstrained optimization. Elsevier, Amsterdam.
Manly, B. F. J. (1973) Validity of the quadratic fitness function.Nature New Biol. 242: 128.
O’Donald, P. (1968) Measuring the intensity of natural selection.Nature 220: 197–8.
O’Donald, P. (1970) Change of fitness by selection for a quantitative character.Theor. Pop Biol. 1: 219–32.
O’Donald, P. (1971) Natural selection for quantitative characters.Heredity 27: 137–53.
O’Donald, P. (1973) Validity of the quadratic fitness function.Nature New Biol. 244: 224.
Osborne, M. R. (1969) Gauss and modified Gauss methods for non-linear least squares methods. InLeast squares methods in data analysis (Edits.R.S. Anderssen andM.R. Osborne). Aust. National Univ., Canberra.
Rao, C. R. (1952)Advanced statistical methods in biometric research, Wiley, New York.
Reed, T. E. andW. J. Schull (1968) A general maximum likelihood estimation program.Amer. J. Hum. Genet. 20: 579–80.