Genome analysis with the conditional multinomial distribution profile
نویسندگان
چکیده
منابع مشابه
A conditional predictive p-value to compare a multinomial with an overdispersed multinomial in the analysis of T-cell populations
Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, w...
متن کاملMultinomial classification with class-conditional overlapping sparse feature groups
Regularized multinomial logistic model is widely used in multi-class classification problems. For high dimension data, various regularization methods achieving sparsity have been developed and applied successfully to many real-world applications such as bioinformatics, health informatics and text mining. In many cases there exist intrinsic group structures among the features. Incorporating the ...
متن کاملThe multinomial distribution on rooted labeled forests
For a probability distribution (ps; s 2 S) on a nite set S, call a random forest F of rooted trees labeled by S (with edges directed away from the roots) a p-forest if given F has m edges the vector of out-degrees of vertices of F has a multinomial distribution with parameters m and (ps; s 2 S), and given also these out-degrees the distribution of F is uniform on all forests with the given out-...
متن کاملParameter Estimation for the Dirichlet-Multinomial Distribution
In the 1998 paper entitled Large Cluster Results for Two Parametric Multinomial Extra Variation Models, Nagaraj K. Neerchal and Jorge G. Morel developed an approximation to the Fisher information matrix used in the Fisher Scoring algorithm for finding the maximum likelihood estimates of the parameters of the Dirichlet-multinomial distribution. They performed simulation studies comparing the res...
متن کاملBayesian Test of Significance for Conditional Independence: The Multinomial Model
Conditional independence tests have received special attention lately in machine learning and computational intelligence related literature as an important indicator of the relationship among the variables used by their models. In the field of probabilistic graphical models, which includes Bayesian network models, conditional independence tests are especially important for the task of learning ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Theoretical Biology
سال: 2011
ISSN: 0022-5193
DOI: 10.1016/j.jtbi.2010.11.034