112 citations · 295 across the 11 of their papers we have counts for
12 papers
Bayes factor functions for reporting outcomes of hypothesis tests
Valen E. Johnson, Sandipan Pramanik, Rachael Shudde
Bayes factors represent the ratio of probabilities assigned to data by competing scientific hypotheses. Drawbacks of Bayes factors are their dependence on prior specifications that…
Using the left Gram matrix to cluster high dimensional data
Shahina Rahman, Valen E. Johnson, Suhasini Subba Rao
For high dimensional data, where P features for N objects (P >> N) are represented in an NxP matrix X, we describe a clustering algorithm based on the normalized left Gram matrix,…
A Fast Algorithm for Clustering High Dimensional Feature Vectors
Shahina Rahman, Valen E. Johnson
We propose an algorithm for clustering high dimensional data. If features for objects are represented in an matrix , where , the method is base…
A Modified Sequential Probability Ratio Test
Sandipan Pramanik, Valen E. Johnson, Anirban Bhattacharya
We describe a modified sequential probability ratio test that can be used to reduce the average sample size required to perform statistical hypothesis tests at specified levels of…
On the Existence of Uniformly Most Powerful Bayesian Tests With Application to Non-Central Chi-Squared Tests
Amir Nikooienejad, Valen E. Johnson
Uniformly most powerful Bayesian tests (UMPBT's) are an objective class of Bayesian hypothesis tests that can be considered the Bayesian counterpart of classical uniformly most pow…
Bayesian Variable Selection For Survival Data Using Inverse Moment Priors
Amir Nikooienejad, Wenyi Wang, Valen E. Johnson
Efficient variable selection in high-dimensional cancer genomic studies is critical for discovering genes associated with specific cancer types and for predicting response to treat…