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Manual for psimpoll and pscomb

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Menu M: data analyses

Menu Md: principal components
Md.3 produces the submenu for data transformations: this is identical to that described for zonation (menu Mc.5). Square-root transformation is routinely used with covariance matrices for the standard pollen data PCA. For proportional data, centred log ratio) is probably the most desirable statistically, using a method recommended by Aitchison (1986) specifically for compostional data such as pollen percentages. It works by transforming the data values to log(value / geometric mean of all values in the sample), and then calculating covariances in the usual way to derive the basic matrix. I know of no use of this in the palynological literature (yet!). Because this method takes log values, zero data entries cannot be used. For proportional data, I treat zeroes as `trace zeroes': values that are not absolute zero, but only seen as zero at the detection level of the count. I use a value of 0.001 as the rounding error (0.5 × 1 / 500), assuming that 500 is a typical pollen count. For other data types, the centred log ratio method calculates log(x + 1). I have not yet tried PCAs with the other two transformation methods (taken from CONISS [Grimm 1987]: see under zonation).

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Copyright © 1995-2007 K.D. Bennett

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