-
作者：Qin, Yichen; Priebe, Carey E.
作者单位：Johns Hopkins University
摘要：We introduce a maximum Lq-likelihood estimation (MLqE) of mixture models using our proposed expectation-maximization (EM) algorithm, namely the EM algorithm with Lq-likelihood (EM-Lq). Properties of the MLqE obtained from the proposed EM-Lq are studied through simulated mixture model data. Compared with the maximum likelihood estimation (MLE), which is obtained from the EM algorithm, the MLqE provides a more robust estimation against outliers for small sample sizes. In particular, we study the...
-
作者：Wheldon, Mark C.; Raftery, Adrian E.; Clark, Samuel J.; Gerland, Patrick
作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Colorado System; University of Colorado Boulder; University of Witwatersrand
摘要：Current methods for reconstructing human populations of the past by age and sex are deterministic or do not formally account for measurement error. We propose a method for simultaneously estimating age-specific population counts, fertility rates, mortality rates, and net international migration flows from fragmentary data that incorporates measurement error. Inference is based on joint posterior probability distributions that yield fully probabilistic interval estimates. It is designed for the...
-
作者：Ma, Li
作者单位：Duke University
摘要：In many case-control studies, a central goal is to test for association or dependence between the predictors and the response. Relevant covariates must be conditioned on to avoid false positives and loss in power. Conditioning on covariates is easy in parametric frameworks such as the logistic regression-by incorporating the covariates into the model as additional variables. In contrast, nonparametric methods such as the Cochran-Mantel-Haenszel test accomplish conditioning by dividing the data...
-
作者：Wang, Huixia Judy; Li, Deyuan
作者单位：North Carolina State University; Fudan University
摘要：The estimation of extreme conditional quantiles is an important issue in numerous disciplines. Quantile regression (QR) provides a natural way to capture the covariate effects at different tails of the response distribution. However, without any distributional assumptions, estimation from conventional QR is often unstable at the tails, especially for heavy-tailed distributions due to data sparsity. In this article, we develop a new three-stage estimation procedure that integrates QR and extrem...
-
作者：Murray, Jared S.; Dunson, David B.; Carin, Lawrence; Lucas, Joseph E.
作者单位：Duke University; Duke University; Duke University
摘要：Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models accommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables, the latent variables typically influence both the dependence structure and the form of the marginal...
-
作者：Ho, Man-Wai; Tu, Wanzhu; Ghosh, Pulak; Tiwari, Ram C.
作者单位：National University of Singapore; Indiana University System; Indiana University Bloomington; Indian Institute of Management (IIM System); Indian Institute of Management Bangalore; US Food & Drug Administration (FDA)
摘要：In cluster randomized trials, patients seen by the same physician are randomized to the same treatment arm as a group. Besides the natural clustering of patients due to cluster/group randomization, interactions between an individual patient and the attending physician within the group could just as well influence patient care outcomes. Despite the intuitive relevance of these interactions to treatment assessment, few studies have thus far examined their influences. Whether and to what extent t...
-
作者：Linzer, Drew A.
作者单位：Emory University
摘要：I present a dynamic Bayesian forecasting model that enables early and accurate prediction of U.S. presidential election outcomes at the state level. The method systematically combines information from historical forecasting models in real time with results from the large number of state-level opinion surveys that are released publicly during the campaign. The result is a set of forecasts that are initially as good as the historical model, and then gradually increase in accuracy as Election Day...
-
作者：Davidian, Marie
作者单位：North Carolina State University
-
作者：Hahn, P. Richard; Carvalho, Carlos M.; Mukherjee, Sayan
作者单位：University of Chicago; University of Texas System; University of Texas Austin; Duke University; Duke University
摘要：We develop a modified Gaussian factor model for the purpose of inducing predictor-dependent shrinkage for linear regression. The new model predicts well across a wide range of covariance structures, on real and simulated data. Furthermore, the new model facilitates variable selection in the case of correlated predictor variables, which often stymies other methods.
-
作者：Martin, Ryan; Liu, Chuanhai
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Purdue University System; Purdue University
摘要：This is to provide corrections to Theorems 1 and 3 in Martin and Liu (2013). The latter correction also casts further light on the role of nested predictive random sets.
