Description Usage Arguments Details Value Author(s) References See Also Examples
A modified version of function EMICM
in package Icens
by incorporating function Aintmap
in package interval
. By defult, the function provides an NPMLE for the distribution function of the survival time.
1 2 | ModifiedEMICM(A, EMstep = TRUE, ICMstep = TRUE, keepiter = FALSE,
tol = 1e-06, maxiter = 1000)
|
A |
an n by 2 matrix with containing the end points of censoring intervals of the format (Li, Ri]. |
EMstep |
a boolean variable indicating whether to take an EM step in the iteration when estimating the common distribution function. The default is TRUE. |
ICMstep |
a boolean variable indicating whether to take an ICM step in the iteration when estimating the common distribution function. The default is TRUE. |
keepiter |
TRUE/FALSE determining whether to keep the iteration states. |
tol |
the maximal L1 distance between successive estimates before stopping iteration when estimating the common distribution function. The default is 1.0e-6. |
maxiter |
the maximal number of iterations to perform before stopping when estimating the common distribution function. The default is 1000. |
After incorporating function Aintmap
, function ModifiedEMICM
often produces intmap
with smaller size than function EMICM
, especially when exact observations (L_i = R_i) exist. In addition, object ppairs
is returned for later use in computing the test statistics in functions gLRT1
, gLRT2
, gLRT3
, gLRT4
, and ScoreTest
. Also, a bug was identified in using EMICM
when ICMstep=F is specified. The problem is fixed by calling ModifiedEMICMmac
, a modified version of function EMICMmac
from package Icens
.
Either EM, ICM, or both steps can be taken in the estimation. When ICMstep = FALSE
, the function computes a self-consistent estimate, the same results as obtained from function icfit
in package interval
.
An object containing the following components:
pf |
Estimated probabilities |
sigma |
NPMLE/self-consistant estimate of the distribution function |
weights |
the diagonal of the likelihood functions's second derivative |
lastchange |
a vector of differences between the last two iterations |
numiter |
number of iterations performed |
iter |
only present if |
intmap |
the real representation associated with the probabilities reported in |
startend |
the indices for L_i and R_i identifying the end points in |
Qiang Zhao and Jianguo Sun
Function EMICM
by Alain Vandal and Robert Gentleman .
J. A. Wellner and Y. Zhan (1997), "A hybrid algorithm for computation of the nonparametric maximum likelihood estimator from censored data", JASA.
1 2 3 4 5 | data(diabetes)
ModifiedEMICM(diabetes[,1:2])
data(cosmesis)
ModifiedEMICM(cosmesis[,1:2])
|
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