Zobrazeno 1 - 10
of 192
pro vyhledávání: '"Craiu, Radu V"'
Copula-based dependence modelling often relies on parametric formulations. This is mathematically convenient but can be statistically inefficient if the parametric families are not suitable for the data and model in focus. To improve the flexibility
Externí odkaz:
http://arxiv.org/abs/2412.09539
Autor:
Herrera-Martin, Antonio, Craiu, Radu V., Eadie, Gwendolyn M., Stenning, David C., Bingham, Derek, Gaensler, Bryan M., Pleunis, Ziggy, Scholz, Paul, Mckinven, Ryan, Kharel, Bikash, Masui, Kiyoshi W.
An important task in the study of fast radio bursts (FRBs) remains the automatic classification of repeating and non-repeating sources based on their morphological properties. We propose a statistical model that considers a modified logistic regressi
Externí odkaz:
http://arxiv.org/abs/2410.17474
Autor:
Dong, Fengqiu Adam, Herrera-Martin, Antonio, Stairs, Ingrid, Craiu, Radu V., Crowter, Kathryn, Eadie, Gwendolyn M., Fonseca, Emmanuel, Good, Deborah, Mckee, James W., Meyers, Bradley W., Pearlman, Aaron B., Stenning, David C.
Studying transient phenomena, such as individual pulses from pulsars, has garnered considerable attention in the era of astronomical big data. Of specific interest to this study are Rotating Radio Transients (RRATs), nulling, and intermittent pulsars
Externí odkaz:
http://arxiv.org/abs/2406.04597
Autor:
Esquivel, J. Arturo, Shen, Yunyi, Leos-Barajas, Vianey, Eadie, Gwendolyn, Speagle, Joshua, Craiu, Radu V, Medina, Amber, Davenport, James
We present a hidden Markov model (HMM) for discovering stellar flares in light curve data of stars. HMMs provide a framework to model time series data that are not stationary; they allow for systems to be in different states at different times and co
Externí odkaz:
http://arxiv.org/abs/2404.13145
Autor:
Craiu, Radu V., Meng, Xiao-Li
This review paper is intended for the Handbook of Markov chain Monte Carlo's second edition. The authors will be grateful for any suggestions that could perfect it.
Externí odkaz:
http://arxiv.org/abs/2401.02518
Autor:
Craiu, Radu V., Levi, Evgeny
Rich data generating mechanisms are ubiquitous in this age of information and require complex statistical models to draw meaningful inference. While Bayesian analysis has seen enormous development in the last 30 years, benefitting from the impetus gi
Externí odkaz:
http://arxiv.org/abs/2210.03243
We propose a copula-based extension of the hidden Markov model (HMM) which applies when the observations recorded at each time in the sample are multivariate. The joint model produced by the copula extension allows decoding of the hidden states based
Externí odkaz:
http://arxiv.org/abs/2207.04127
This article proposes a set of categories, each one representing a particular distillation of important statistical ideas. Each category is labeled a "sense" because we think of these as essential in helping every statistical mind connect in construc
Externí odkaz:
http://arxiv.org/abs/2204.05313
Multi-collinearity is a wide-spread phenomenon in modern statistical applications and when ignored, can negatively impact model selection and statistical inference. Classic tools and measures that were developed for "$n>p$" data are not applicable no
Externí odkaz:
http://arxiv.org/abs/2203.10360
We identify recurrent ingredients in the antithetic sampling literature leading to a unified sampling framework. We introduce a new class of antithetic schemes that includes the most used antithetic proposals. This perspective enables the derivation
Externí odkaz:
http://arxiv.org/abs/2110.15124