Results 61 to 70 of about 85,479 (297)
Approaches to evaluating measurement uncertainty [PDF]
International Journal of Metrology and Quality Engineering, 2012 The Guide to the expression of measurement uncertainty, (GUM, JCGM 100) and its Supplement 1: propagation of distributions by a Monte Carlo method, (GUMS1, JCGM 101) are two of the most widely used documents concerning ...
Forbes A.B.
doaj +1 more source
Markov chain Monte Carlo, recent developments
, 2005 only:\ud \ud There has recently been an explosion of interest in Markov chain Monte Carlo (MCMC) for biostatistical modeling and analysis, particularly, but not exclusively in a Bayesian framework.
K. Mengersen, Mengersen, Kerrie L.
core +1 more source
Efficacy, safety and cost‐effectiveness of CAR‐T therapy
British Journal of Clinical Pharmacology, EarlyView.CAR T‐cells demonstrate high efficacy in blood cancers, including ALL, MM and DLBCL. Innovations target solid tumours despite challenges such as antigen escape. Combination therapies enhance the delivery and infiltration of CAR T cells. Toxicity, cost and resistance remain major barriers to clinical use.
Emina Karahmet Sher +7 more
wiley +1 more source
Interacting Particle Markov Chain Monte Carlo
, 2016 We introduce interacting particle Markov chain Monte Carlo (iPMCMC), a PMCMC method based on an interacting pool of standard and conditional sequential Monte Carlo samplers. Like related methods, iPMCMC is a Markov chain Monte Carlo sampler on an extended space. We present empirical results that show significant improvements in mixing rates relative to
Doucet, A +6 more
openaire +4 more sources
British Journal of Clinical Pharmacology, EarlyView.Background Aims Pharmacokinetic interaction studies typically focus on oral administration, but intravenous (IV) administration bypasses intestinal degradation and hepatic first‐pass metabolism, leading to distinct drug–drug interaction (DDI) magnitude. This study aimed to develop a predictive model for DDIs involving IV‐administered drugs.
Vianney Tuloup +2 more
wiley +1 more source
MONTE CARLO MARKOV CHAIN (MCMC) STOCHASTIC MODELING OF SUPPLY CHAIN
Annals: Series on engineering sciences (Academy of Romanian Scientists)Effective inventory management in multi-echelon supply chains is challenged by stochastic demand and uncertain lead times, which amplify variability and increase operational costs.
Marcel ILIE, Augustin SEMENESCU
doaj +1 more source
British Journal of Clinical Pharmacology, EarlyView.Aim The number of pregnancies among women with cystic fibrosis (wwCF) has steadily increased over the past decade. However, the pharmacokinetics (PK) of elexacaftor–tezacaftor–ivacaftor (ETI) during gestation remains uncharacterized, despite its widespread use in this population.
Paulette Magnas +16 more
wiley +1 more source
On the importance of including both sexes in animal studies – insights from home‐cage monitoring
Biological Reviews, EarlyView.ABSTRACT A review of behavioural studies using home‐cage monitoring (HCM) systems revealed that over 61% of studies used only male subjects, with only 24% including both sexes, despite evidence of substantial behavioural differences between male and female animals. This bias could influence the outcomes of biomedical research.
Maša Čater +12 more
wiley +1 more source
Distance between configurations in Markov chain Monte Carlo simulations
Journal of High Energy Physics, 2017 For a given Markov chain Monte Carlo algorithm we introduce a distance between two configurations that quantifies the difficulty of transition from one configuration to the other configuration.
Masafumi Fukuma +2 more
doaj +1 more source
Identifying influential observations in Bayesian models by using Markov chain Monte Carlo. [PDF]
, 2011 In statistical modelling, it is often important to know how much parameter estimates are influenced by particular observations. An attractive approach is to re-estimate the parameters with each observation deleted in turn, but this is computationally ...
James Carpenter +5 more
core +1 more source