Zobrazeno 1 - 10
of 19 232
pro vyhledávání: '"Kohn R"'
Autor:
Bradshaw, A.
Publikováno v:
Journal of Medical Ethics, 2002 Aug 01. 28(4), 278-279.
Externí odkaz:
https://www.jstor.org/stable/27718938
We propose a new class of financial volatility models, called the REcurrent Conditional Heteroskedastic (RECH) models, to improve both in-sample analysis and out-ofsample forecasting of the traditional conditional heteroskedastic models. In particula
Externí odkaz:
http://arxiv.org/abs/2010.13061
Autor:
Hauser MJ; Department of Psychiatry, Harvard Medical School, Newton, Massachusetts, USA., Kohn R; Brown University School of Public Health, Providence, Rhode Island, USA.
Publikováno v:
Behavioral sciences & the law [Behav Sci Law] 2024 May-Jun; Vol. 42 (3), pp. 205-220. Date of Electronic Publication: 2024 Mar 08.
The Stochastic Volatility (SV) model and its variants are widely used in the financial sector while recurrent neural network (RNN) models are successfully used in many large-scale industrial applications of Deep Learning. Our article combines these t
Externí odkaz:
http://arxiv.org/abs/1906.02884
Publikováno v:
Phys. Rev. A 99, 033836 (2019)
Harmonic generation from solid surfaces is a promising tool for producing high energy attosecond pulses. We report shaping of the harmonic spectrum to achieve the bandwidth necessary for attosecond pulse generation. The shaping is demonstrated for lo
Externí odkaz:
http://arxiv.org/abs/1901.11147
This article addresses the problem of efficient Bayesian inference in dynamic systems using particle methods and makes a number of contributions. First, we develop a correlated pseudo-marginal (CPM) approach for Bayesian inference in state space (SS)
Externí odkaz:
http://arxiv.org/abs/1612.07072
Estimating copulas with discrete marginal distributions is challenging, especially in high dimensions, because computing the likelihood contribution of each observation requires evaluating $2^{J}$ terms, with $J$ the number of discrete variables. Cur
Externí odkaz:
http://arxiv.org/abs/1608.06174
The pseudo-marginal (PM) approach is increasingly used for Bayesian inference in statistical models, where the likelihood is intractable but can be estimated unbiasedly. %Examples include random effect models, state-space models and data subsampling
Externí odkaz:
http://arxiv.org/abs/1603.02485
Autor:
Kohn R; Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute of Health Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA. Electronic address: rachel.kohn2@pennmedicine.upenn.edu., Ashana DC; Department of Medicine, Duke University, Durham, NC., Vranas KC; Palliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA; Department of Medicine, Oregon Health & Science University, Portland, OR; Center to Improve Veteran Involvement in Care, Portland, OR., Viglianti EM; Department of Internal Medicine, University of Michigan Health System, Ann Arbor, MI; Department of Internal Medicine, VA Ann Arbor, Ann Arbor, MI., Hauschildt K; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD., Chen C; Department of Medicine, University of Texas Southwestern Medical Center, Dallas, TX., Vail EA; Leonard Davis Institute of Health Economics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA., Moroz L; Department of Obstetrics and Gynecology, Yale University, New Haven, CT., Gershengorn HB; Department of Medicine, University of Miami Miller School of Medicine, Miami, FL; Department of Medicine, Albert Einstein College of Medicine, Bronx, NY.
Publikováno v:
Chest [Chest] 2024 Oct; Vol. 166 (4), pp. 765-777. Date of Electronic Publication: 2024 Mar 20.
Publikováno v:
In Journal of Mathematical Psychology June 2020 96