Results 41 to 50 of about 1,202,565 (290)
Optimal Model Averaging for Semiparametric Partially Linear Models with Censored Data
Mathematics, 2023 In the past few decades, model averaging has received extensive attention, and has been regarded as a feasible alternative to model selection. However, this work is mainly based on parametric model framework and complete dataset.
Guozhi Hu, Weihu Cheng, Jie Zeng
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Stochastic average model methods
Computational Optimization and ApplicationsWe consider the solution of finite-sum minimization problems, such as those appearing in nonlinear least-squares or general empirical risk minimization problems. We are motivated by problems in which the summand functions are computationally expensive and evaluating all summands on every iteration of an optimization method may be undesirable.
Matt Menickelly, Stefan M. Wild
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Pediatric Blood &Cancer, EarlyView.ABSTRACT The pediatric hematology‐oncology fellowship training curriculum has not substantially changed since its inception. The first year of training is clinically focused, and the second and third years are devoted to scholarship. However, this current structure leaves many fellows less competitive in the current job market, resulting in ...
Scott C. Borinstein +3 more
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Two-Population Mortality Forecasting: An Approach Based on Model Averaging
RisksThe analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to predict ...
Luca De Mori +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Purpose Metabolic syndrome (MetS) is a common complication in survivors of childhood acute lymphoblastic and myeloid leukemia (AL), and a major risk factor for premature cardiovascular disease, type‐2‐diabetes, and metabolic dysfunction‐associated steatotic liver disease (MASLD).
Visentin Sandrine +10 more
wiley +1 more source
Forecast Bitcoin Volatility with Least Squares Model Averaging
Econometrics, 2019 In this paper, we study forecasting problems of Bitcoin-realized volatility computed on data from the largest crypto exchange—Binance. Given the unique features of the crypto asset market, we find that conventional regression models exhibit strong ...
Tian Xie
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga +56 more
wiley +1 more source
MathematicsBayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques.
Aliaksandr Hubin, Geir Storvik
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Scalable Bayesian model averaging through local information propagation
, 2014 We show that a probabilistic version of the classical forward-stepwise variable inclusion procedure can serve as a general data-augmentation scheme for model space distributions in (generalized) linear models.
Ma, Li
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AVERAGING PROPERTIES AND SPREADING MODELS [PDF]
Journal of the Korean Mathematical Society, 2005 The authors characterize Banach--Saks properties in Banach spaces in terms of spreading models. Theorem~1 is the well-known result [see, e.g., \textit{B.~Beauzamy} and \textit{J.--T.\ Lapresté}, ``Modèles étalés des espaces de Banach'' (Travaux en Cours, Hermann, Paris) (1984; Zbl 0553.46012)]) that \(X\) has the weak Banach--Saks property iff no ...
Cho, Kyugeun, Lee, Chongsung
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