gammasigma: d^2/d_gamma_ldsigma^2

Description

Calculates the Information matrix term of I_eta gamma for one outcome of interest l.

gammasigma(
  l, HL_array, HR_array, tpos_all, obs_all,
  apply_diffs, temp_beta, A_i, xDats, no_l_all,
  no_two_all, gMat, a1, a2, k, d)

The output is a matrix containing the component of the information matrix of the gamma and sigma^2 parameters for outcome l.

l: Index of first outcome of interest.
HL_array: n x K matrix containing all the hazard values for the left times.
HR_array: n x K matrix containing all the hazard values for the right times.
tpos_all: n x k matrix containing a indictor for whether that time is left-censored or not.
obs_all: n x k matrix containing a indictor for whether that time is right-censored or not.
apply_diffs: Matrix containing the differences between survival functions of the left and right time intervals.
temp_beta: vector of fitted coefficients.
A_i: Product of apply_diffs across all outcomes K summed over all quadrature nodes D.
xDats: List of design matrices.
no_l_all: n x (k - 1) matrix containing the product of apply_diffs across all outcomes K excluding the current outcome l.
no_two_all: n x (k - 2) matrix containing the product of apply_diffs across all outcomes k excluding the outcomes l and m.
gMat: n x q matrix of genetic information.
a1: First shape parameter of beta parameter.
a2: Second shape parameter of beta parameter.
k: Total number of outcomes.
d: Number of quadrature nodes.