Results 101 to 110 of about 13,398 (256)
Canadian Journal of Statistics, EarlyView.Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen +3 more
wiley +1 more source
Minimum Penalized ϕ-Divergence Estimation under Model Misspecification
Entropy, 2018 This paper focuses on the consequences of assuming a wrong model for multinomial data when using minimum penalized ϕ -divergence, also known as minimum penalized disparity estimators, to estimate the model parameters.
M. Virtudes Alba-Fernández +2 more
doaj +1 more source
Inference for Iterated GMM Under Misspecification and Clustering
, 2018 This paper develops a new distribution theory and inference methods for over-identified Generalized Method of Moments (GMM) estimation focusing on the iterated GMM estimator, allowing for moment misspecification, and for clustered dependence with ...
Lee, Seojeong ; https://orcid.org/ +3 more
core +1 more source
The impact of covariance misspecification in risk-based portfolios [PDF]
, 2017 The equal-risk-contribution, inverse-volatility weighted, maximum-diversification and minimum-variance portfolio weights are all direct functions of the estimated covariance matrix. We perform a Monte Carlo study to assess the impact of covariance matrix
Gagnon-Fleury, Jean-Philippe +10 more
core +1 more source
Complexity and Misspecification
We propose a tractable model of repeated decision problems that combines concern about model misspecification, as in robust control, with a complexity cost, such as Shannon entropy, that makes pessimistic beliefs trade off statistical plausibility against simplicity. In a static setting, stronger complexity aversion selects more concentrated worst-case
Fudenberg, Drew, Mudekereza, Florian
openaire +2 more sources
Vine copula knockoffs for variable selection in gene expression studies
Canadian Journal of Statistics, EarlyView.Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina +3 more
wiley +1 more source
CPT: Pharmacometrics & Systems PharmacologyWe address the problem of model misspecification in population pharmacokinetics (PopPK), by modeling residual unexplained variability (RUV) by machine learning (ML) methods in a postprocessing step after conventional model building. The practical purpose
Christos Kaikousidis +2 more
doaj +1 more source
Frontiers in Psychology, 2018 The performance of the limited-information statistic M2 for diagnostic classification models (DCMs) is under-investigated in the current literature. Specifically, the investigations of M2 for specific DCMs rather than general modeling frameworks are ...
Fu Chen, Yanlou Liu, Tao Xin, Ying Cui
doaj +1 more source
Sparse maximum likelihood estimation of regression models
Canadian Journal of Statistics, EarlyView.Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley +1 more source
Detecting Model Misspecification in Bayesian Piecewise Growth Models
Supplemental Materials for a Manuscript Titled: "Detecting Model Misspecification in Bayesian Piecewise Growth ...
Sarah Depaoli, Fan Jia, Ihnwhi Heo
core +1 more source