Results 131 to 140 of about 48,781 (279)
Precise asymptotics on spectral statistics of random matrices
Journal of the Korean Statistical Society, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Rank‐based estimation of propensity score weights via subclassification
Canadian Journal of Statistics, EarlyView.Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang +3 more
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Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP
Canadian Journal of Statistics, EarlyView.Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang +5 more
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Canadian Journal of Statistics, EarlyView.Abstract We establish the consistency and the asymptotic distribution of the least squares estimators of the coefficients of a subset vector autoregressive process with exogenous variables (VARX). Using a martingale central limit theorem, we derive the asymptotic normal distribution of the estimators. Diagnostic checking is discussed using kernel‐based
Pierre Duchesne +2 more
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Precise small deviations in L 2 of some Gaussian processes appearing in the regression context
Open Mathematics, 2014 Kirichenko Alisa, Nikitin Ya.
doaj +1 more source
On the Precise Asymptotics of Universal Inference
In statistical inference, confidence set procedures are typically evaluated based on their validity and width properties. Even when procedures achieve rate-optimal widths, confidence sets can still be excessively wide in practice due to elusive constants, leading to extreme conservativeness, where the empirical coverage probability of nominal $1-α ...
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Bayesian inverse ensemble forecasting for COVID‐19
Canadian Journal of Statistics, EarlyView.Abstract Variations in strains of COVID‐19 have a significant impact on the rate of surges and on the accuracy of forecasts of the epidemic dynamics. The primary goal for this article is to quantify the effects of varying strains of COVID‐19 on ensemble forecasts of individual “surges.” By modelling the disease dynamics with an SIR model, we solve the ...
Kimberly Kroetch, Don Estep
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A goodness‐of‐fit test for regression models with discrete outcomes
Canadian Journal of Statistics, EarlyView.Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang +2 more
wiley +1 more source
Precise asymptotics for large deviations of integral forms
, 2012 For suitable families of locally infinitely divisible Markov processes $\{ ^{ }_t\}_{0\leq t\leq T}$ with frequent small jumps depending on a small parameter $ >0,$ precise asymptotics for large deviations of integral forms $\mathbb{E}^ [\exp\{ ^{-1}F( ^ )\}]$ are proved for smooth functionals $F.$ The main ingredient of the proof in this ...
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