Perform Group Sparse O2PLS
so2m_group(
X,
Y,
n,
nx,
ny,
groupx = NULL,
groupy = NULL,
keepx = NULL,
keepy = NULL,
tol = 1e-10,
max_iterations = 1000,
max_iterations_sparsity = 1000
)A list containing
Joint \(X\) scores
Joint \(X\) loadings
Joint \(Y\) scores
Joint \(Y\) loadings
Orthogonal \(X\) scores
Orthogonal \(X\) loadings
Orthogonal \(X\) weights
Orthogonal \(Y\) scores
Orthogonal \(Y\) loadings
Orthogonal \(Y\) weights
Regression coefficient in Tt ~ U
Regression coefficient in U ~ Tt
Residuals in Tt in Tt ~ U
Residuals in U in U ~ Tt
Joint weights of X variables at group level. They are the norms of the X-joint loadings per group
Joint weights of Y variables at group level. They are the norms of the Y-joint loadings per group
Numeric matrix. Vectors will be coerced to matrix with as.matrix (if this is possible)
Numeric matrix. Vectors will be coerced to matrix with as.matrix (if this is possible)
Integer. Number of joint PLS components. Must be positive.
Integer. Number of orthogonal components in \(X\). Negative values are interpreted as 0
Integer. Number of orthogonal components in \(Y\). Negative values are interpreted as 0
Vector. Used when sparse = TRUE. A vector of strings indicating group names of each X-variable. Its length must be equal to the number of variables in \(X\). The order of group names must corresponds to the order of the variables.
Vector. Used when sparse = TRUE. A vector of strings indicating group names of each Y-variable. The length must be equal to the number of variables in \(Y\). The order of group names must corresponds to the order of the variables.
Vector. Used when sparse = TRUE. A vector of length n indicating how many variables (or groups if groupx is provided) to keep in each of the joint component of \(X\). If the input is an integer, all the components will have the same amount of variables or groups retained.
Vector. Used when sparse = TRUE. A vector of length n indicating how many variables (or groups if groupx is provided) to keep in each of the joint component of \(Y\). If the input is an integer, all the components will have the same amount of variables or groups retained.
Double. Threshold for which the NIPALS method is deemed converged. Must be positive.
Integer. Maximum number of iterations for the NIPALS method.
Integer. Used when sparse = TRUE. Maximum number of iterations for the NIPALS method for GO2PLS.
o2m