Titlebook: Analyzing Ecological Data; Alain F. Zuur,Elena N. Ieno,Graham M. Smith Book 2007 The Editor(s) (if applicable) and The Author(s), under ex

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Srikanta Patnaik,Xin-She Yang,Feng Qiaon-linearity and interaction between explanatory variables than regression, generalised linear models and generalised additive models, and can be used to find interactions missed by other methods. They also indicate the relative importance of different explanatory variables and are useful in analysing residuals from linear regression, GLM or GAM.

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https://doi.org/10.1057/9781137405579 do this, the seasonal component needs to be determined and dealt with in some way. We will discuss three methods, of increasing mathematical complexity, for estimating common patterns in time series. In the last section, we discuss a technique that can be used to identify sudden changes.

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https://doi.org/10.1007/978-3-658-11914-0erature, moisture, soil nutrients, and subsurface geology. Spatially continuous data are often referred to as . (Bailey and Gatrell 1995). The set of statistical techniques that can be used for analysing and modelling this type of data is called ..

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Principal coordinate analysis and non-metric multidimensional scaling,od that, just like PCA, is based on an eigenvalue equation, but it can use any measure of association (Chapter 10). Just like PCA, the axes are plotted against each other in a Euclidean space, but the PCoA does not produce a biplot (a joint plot of the variables and observations).

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