The package robustETM consists of the functions to perform pseudolikelihood based EM test for homogeneity in generalized exponential tilt mixture models.
Motivated by analyses of DNA methylation data, we propose a semiparametric mixture model, namely the generalized exponential tilt mixture model,
to account for heterogeneity between differentially methylated and non-differentially methylated subjects in the cancer group, and capture the
differences in higher order moments (e.g. mean and variance) between subjects
in cancer and normal groups. A pairwise pseudolikelihood is constructed
to eliminate the unknown nuisance function. To circumvent boundary and
non-identifiability problems as in parametric mixture models, we modify the
pseudolikelihood by adding a penalty function. In addition, test with simple
asymptotic distribution has computational advantages over permutational
test for high-dimensional genetic and epigenetic data. We propose a pseudolikelihood
based expectation-maximization test, and show the proposed test
follows a simple chi-squared limiting distribution.
The methods contains in function sim are:
The proposed PLEMT test (pseudolikelihood based EM test)
The modified empirical likelihood ratio test
The empirical likelihood ratio test
The logistic regression test
The Wilcoxon test
The F test
The KS test
Hao Wu Maintainer: Chuan Hong <firstname.lastname@example.org>
Hong, C., Chen Y., Ning Y., Wang S., Wu H. and Carroll R.J. (2016). PLEMT: A novel pseudolikelihood based EM test for homogeneity in generalized exponential tilt mixture model (in preparation).
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