sd_off: d^2/d_theta_kdsigma^2

In SIMICO: Set-Based Inference for Multiple Interval-Censored Outcomes

d^2/d_theta_kdsigma^2

Description

Calculates the Information matrix term of I_theta sigma^2 for outcomes l and m.

Usage

sd_off(l, m, phen_l, phen_m, temp_beta, d, apply_diffs, A_i,
   HL_array, HR_array, no_l_all, no_two_all, tpos_all, obs_all, k)

Arguments

l	Index of first outcome of interest.
m	Index of second outcome of interest.
phen_l	List containing the left and right design matrices and interval times for outcome l.
phen_m	List containing the left and right design matrices and interval times for outcome m.
temp_beta	vector of fitted coefficients.
d	Total number of quadrature nodes.
apply_diffs	Matrix containing the differences between survival functions of the left and right time intervals.
A_i	Product of apply_diffs across all outcomes k summed over all quadrature nodes d.
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.
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 outcomes l and m.
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.
k	Total number of outcomes.

Value

The output is a matrix containing the component of the information matrix of the sigma and theta parameters.

SIMICO documentation built on Nov. 26, 2022, 1:06 a.m.