Results 41 to 50 of about 8,463,541 (194)
Generating functions and short recursions, with applications to the moments of quadratic forms in noncentral normal vectors [PDF]
Using generating functions, the top-order zonal polynomials that occur in much distribution theory under normality can be recursively related to other symmetric functions (power-sum and elementary symmetric functions, Ruben, Hillier, Kan, and Wang ...
Grant Hillier, Xiaolu Wang, Raymond Kan
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Exact enumeration of satisfiable 2-SAT formulae
, 2022 We obtain exact expressions counting the satisfiable 2-SAT formulae and describe the structure of associated implication digraphs. Our approach is based on generating function manipulations.
Dovgal, Sergey +2 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To characterize the demographic, clinical, and laboratory features of the Chinese patients of genetic Creutzfeldt‐Jakob disease with T188K variant (T188K‐gCJD), the most common subtype of genetic prion diseases (gPrDs) in China. Methods In this nationwide retrospective study, data from 98 genetically confirmed T188K‐gCJD patients ...
Chun‐Jie Li +11 more
wiley +1 more source
Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples [PDF]
A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ...
Ben Jann
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Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
wiley +1 more source
Reserves, Injury Severity, and Outcomes in Traumatic Brain Injury: A CENTER‐TBI Observational Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Reserve refers to the brain's ability to maintain function after an injury and strongly relates to traumatic brain injury (TBI) outcomes. This study examined (1) whether associations between pre‐injury reserve proxies and outcomes differed across injury severity categories, and (2) whether the impact of injury severity varied across ...
Natascha Ekdahl +6 more
wiley +1 more source
Computational and theoretical aspects of iterated generating functions [PDF]
, 2013 The thesis offers an investigation into the analysis of so-called iterated generating functions and the schemes that produce them. Beginning with the study of some ad hoc scheme formulations, the notion of an iterated generating function is introduced ...
Clapperton, James Anthony
core +1 more source
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Arthritis Care &Research, EarlyView.Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective The objective of this study was to estimate the minimal important change (MIC) and minimal clinically important difference (MCID) for pain and physical function in individuals with hip osteoarthritis (OA) following a physiotherapist‐guided exercise intervention.
Yareni Guerrero +8 more
wiley +1 more source
Exact Probabilistic Inference Using Generating Functions
, 2023 Probabilistic programs are typically normal-looking programs describing posterior probability distributions. They intrinsically code up randomized algorithms and have long been at the heart of modern machine learning and approximate computing. We explore
Klinkenberg, Lutz +3 more
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