Generalized discriminant analysis based on distances

By Marti J. Anderson, John Robinson. 2003

763 citations recorded by the source corpus.

Subfields: Genetics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/23692750e11d8ddc21555a4ae4adb3cc76948b46

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Citations in the corpus

Molluscan assemblages of seagrass-covered and bare intertidal flats on the Banc d'Arguin, Mauritania, in relation to characteristics of sediment and organic matter (2008, methodology): “Toadjustforalimitednumber of permutations, the Monte Carlo asymptotic P -value was used (Anderson and Robinson, 2003).”
Leading role of the sea urchin Arbacia lixula in maintaining the barren state in southwestern Mediterranean (2011, methodology): “Differences in benthic assemblages among the experimental conditions (P?A?; P?A-; P-A?; and P-A-) were assessed through a permutational MANOVA (Anderson 2001) where asymptotic p values were estimated by Monte Carlo re-sampling (Anderson and Robinson 2003).”
Discriminating Groups of Organisms (2010, methodology): “Some recently developed methods for performing discriminant analysis with relatively small sample sizes (e.g. Anderson and Robinson 2003; Howland and Park 2004; Ye et al. 2004) seem promising, but none have yet been applied to morphometric data.”
Intertidal assemblages on artificial and natural habitats in marinas on the north-west coast of Italy (2004, methodology): “When there were too few permutations to obtain a meaningful P value in a posteriori comparisons, 4,999 random Montecarlo draws from the asymptotic permutation distribution were used ( Anderson and Robinson 2004; M.J.”
Structure of cryptic reef fish assemblages: relationships with habitat characteristics and predator density (2003, neutral): “The relative distinctiveness of the assemblages is also demonstrated well by the differences in the leave-one-out allocation success from the CAP analysis (Table 3; Lachenbruch & Mickey 1968, Anderson & Willis 2003).”
A distance-based framework for measuring functional diversity from multiple traits. (2010, methodology): “For example, the use of PCoA axes as variables has already been presented in the context of multivariate analysis of variance (Legendre and Anderson 1999) and general discriminant analysis (Anderson and Robinson 2003).”
Multivariate and univariate asymmetrical analyses in environmental impact assessment: a case study of Mediterranean subtidal sessile assemblages (2005, methodology): “For some terms in the analysis, there were not enough permutable units to get a reasonable test by permutation, so a p-value was obtained using a Monte Carlo random sample from the asymptotic permutation distribution (Anderson & Robinson 2003, see Eq.”
Protection from fishing alters the species composition of fish assemblages in a temperate-tropical transition zone (2007, methodology): “The CAP procedure has been shown to be more powerful than PERMANOVA for situations where group differences occur in a different direction in the multivariate space than the direction of greatest overall variation ( Anderson and Robinson 2003 ).”
Drill-cored rock pools: An effective method of ecological enhancement on artificial structures (2016, methodology): “For the asymmetrical PERMANOVA analysis there were not enough possible permutations to perform a reasonable test of significance, therefore Monte Carlo P values were used as a more meaningful, but approximate, alternative (Anderson and Robinson 2003).”
Partitioning the diversity of riverine fish: The roles of habitat types and non-native species (2007, methodology): “I used canonical analysis of principal coordinates (CAP), a recently developed constrained ordination technique (Anderson & Robinson, 2003; Anderson & Willis, 2003), to test the null hypothesis of no differences in fish assemblage composition between the a priori established habitat types.”
Descending to the twilight-zone: changes in coral reef fish assemblages along a depth gradient down to 65 m (2008, methodology): “To test for a change in assemblages along gradients of both depth and habitat variables we used a Canonical Analysis of Principal Coordinates (CAP, following Anderson & Willis 2003).”