Convex linear combinations of compositions

被引:19
作者
Aitchison, J [1 ]
Bacon-Shone, J
机构
[1] Univ Glasgow, Dept Stat, Glasgow G12 8QQ, Lanark, Scotland
[2] Univ Hong Kong, Social Sci Res Ctr, Hong Kong, Peoples R China
关键词
Dirichlet distribution; end-member problem; lattice testing of hypotheses; logistic normal distribution; mixing of compositions; multivariate skew normal distribution;
D O I
10.1093/biomet/86.2.351
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
When a sampled target composition is suspected of being a mixture of different compositions from a number of independent sources the question of the nature of the mixing mechanism arises. For the resolution of this question several models involving convex linear mixtures of compositions are considered and in particular the distributional problem of describing the pattern of variability of the target compositions, given information about the source distributions, is resolved in terms of approximations involving logistic normal and logistic skew normal distributions. The quality of these approximations is shown to be satisfactory through a series of simulations briefly reported. The modelling and subsequent statistical inference are motivated by an illustrative application to investigating the nature of pollution at three fishing locations in a Scottish loch.
引用
收藏
页码:351 / 364
页数:14
相关论文
共 13 条
  • [1] MEASURES OF LOCATION OF COMPOSITIONAL DATA SETS
    AITCHISON, J
    [J]. MATHEMATICAL GEOLOGY, 1989, 21 (07): : 787 - 790
  • [2] LOGISTIC-NORMAL DISTRIBUTIONS - SOME PROPERTIES AND USES
    AITCHISON, J
    SHEN, SM
    [J]. BIOMETRIKA, 1980, 67 (02) : 261 - 272
  • [3] Aitchison J, 1997, P IAMG 97 3 ANN C IN, V97, P3
  • [4] Anderson T.W., 1986, STAT ANAL DATA, V2nd
  • [5] The multivariate skew-normal distribution
    Azzalini, A
    DallaValle, A
    [J]. BIOMETRIKA, 1996, 83 (04) : 715 - 726
  • [6] Cramer H., 1946, Mathematical Methods of Statistics
  • [7] Kendall MG., 1948, The advanced theory of statistics, V4
  • [8] KULLBACK S, 1951, ANN MATH STAT, V22, P525
  • [9] LEMAITRE RW, 1982, NUMERICAL PETROGRAPH
  • [10] *MATH WORKS INC, 1996, MATLAB 5