View source: R/compute.kernel.R
compute.kernel | R Documentation |
Compute a kernel from a given data matrix.
compute.kernel(X, kernel.func = "linear", ..., test.pos.semidef = FALSE)
X |
a numeric matrix (or data frame) used to compute the kernel.
|
kernel.func |
the kernel function to use. This parameter can be set to
any user defined kernel function. Widely used kernel functions are
pre-implemented, that can be used by setting |
... |
the kernel function arguments. Valid parameters for pre-implemented kernels are:
|
test.pos.semidef |
boleean. If |
compute.kernel
returns an object of classes "kernel"
, a
list that contains the following components:
kernel |
: the computed kernel matrix. |
X |
: the original dataset. If |
kernel.func |
: the kernel function used. |
kernel.args |
: the arguments used to compute the kernel. |
Jerome Mariette <jerome.mariette@inrae.fr> Nathalie Vialaneix <nathalie.vialaneix@inrae.fr>
Lozupone C. and Knight R. (2005). UniFrac: a new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology, 71(12), 8228-8235.
Lozupone C., Hamady M., Kelley S.T. and Knight R. (2007). Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Applied and Environmental Microbiology, 73(5), 1576-1585.
Witten D. (2011). Classification and clustering of sequencing data using a Poisson model. Annals of Applied Statistics, 5(4), 2493-2518.
combine.kernels
, kernel.pca
data(TARAoceans)
pro.NOGs.kernel <- compute.kernel(TARAoceans$pro.NOGs,
kernel.func = "abundance")
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