View source: R/buildEmptyJac.R
buildEmptyJac | R Documentation |
Prepare an empty Jacobian matrix, with useful entries prefilled. In case of distribution "gaussian", it returns the lhs matrix of the linear system for finding the feature paramters
buildEmptyJac(
n,
m,
lower,
distribution = "quasi",
normal = FALSE,
nLambda1s = 1,
centMat = NULL,
weights = 1
)
n |
the number of parameters |
m |
the dimension |
lower |
the current parameter estimates |
distribution |
A character string, the distributional assumption for the data |
normal |
a boolean, are normalization restrictions in place? |
nLambda1s |
The number of centering restrictions |
centMat |
The centering matrix |
weights |
Vector of feature weights |
an empty jacobian matrix, or the lhs of the system of estimating equations
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