View source: R/F_NBjacobianRow.R
NBjacobianRow | R Documentation |
A jacobian function of the NB for the row scores
NBjacobianRow(
beta,
X,
reg,
thetas,
muMarg,
k,
n,
p,
rowWeights,
nLambda,
rMatK,
preFabMat,
Jac,
allowMissingness,
naId
)
beta |
a vector of of length n + k +1 regression parameters to optimize |
X |
the data matrix of dimensions nxp |
reg |
a 1xp regressor matrix: outer product of column scores and psis |
thetas |
nxp matrix with the dispersion parameters (converted to matrix for numeric reasons) |
muMarg |
an nxp offset matrix |
k |
a scalar, the dimension of the RC solution |
n |
a scalar, the number of samples |
p |
a scalar, the number of taxa |
rowWeights |
a vector of length n, the weights used for the restrictions |
nLambda |
an integer, the number of lagrangian multipliers |
rMatK |
the lower dimension row scores |
preFabMat |
a prefab matrix, (1+X/thetas) |
Jac |
an empty Jacobian matrix |
allowMissingness |
A boolean, are missing values present |
naId |
The numeric index of the missing values in X |
a symmetric jacobian matrix of size n+k + 1
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