Description Usage Arguments Value Author(s) See Also
This function takes current parameters and observed data, gives an updated patient level clustering.
1 2 3 4 5 6 |
Beta |
current patient level linear coefficients matrix |
Gamma |
current site level linear coefficients array |
w |
current patient level clustering prior prob, a vector |
X |
the patient level covariate matrix |
Y |
the CAL observation matrix, with missing values |
Z |
the site level covariate matrix |
delta |
the missing indicator matrix, with 1 means missing |
E |
current patient level clustering vector |
R |
current site level clustering matrix |
S |
number of patient level clusters |
Ds |
a vector recording numbers of site level clusters |
mu |
current estimated mean matrix for CAL |
mustar |
current matrix of latent value for missingness model |
sigma |
current estimated noise variance |
c |
current c for missingness model. It is a vector |
n |
number of patients |
m |
number of sites |
T0 |
number of teeth |
p |
dimension of patient level covariates |
q |
dimension of site level covariates |
D |
the D matrix in the paper |
updateE( Beta, Gamma,w, X, Y, Z, delta,E, R, S, Ds, mu, mustar, sigma, c, n, m, T0, p, q, D)
returns a list with following variables:
E |
the updated patient level clustering |
Ds |
new vector recording the numbers of site level clusters |
mu |
the updated mu computed by updated E |
mustar |
the updated mustar computed by updated E |
Yuliang Li
update_RJ for a complete example for all functions in this package.
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