Results 141 to 150 of about 2,404,671 (311)

Non-negative demand in newsvendor models:The case of singly truncated normal samples

This paper considers the classical newsvendor model when demand is normally distributed but with a large coefficient of variation. This leads to observe with a non-negligible probability negative values that do not make sense.
Halkos, George, Kevork, Ilias
core  

Inference with the lognormal distribution [PDF]

Several estimators of the expectation, median and mode of the lognormal distribution are derived. They aim to be approximately unbiased, efficient, or have a minimax property in the class of estimators we introduce.
Nicholas Longford
core  

On Fixed Accuracy Confidence Interval in Multivariate Normal Distribution with Order 1 Autoregressive Covariance Structure. [PDF]

J Stat Theory Pract, 2023
Sarkar P, Bandyopadhyay U, Bhattacharya R.   +2 more
europepmc   +1 more source

Clinical performance of the urine‐based TERT promoter AbsoluteQ Digital PCR for non‐invasive detection of bladder cancer

Molecular Oncology, EarlyView.
A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel, Izabela Kubiak, Lena Rutkowska, Żaneta Kasprzyk, Łukasz Kępczyński, Michał Bednarek, Dariusz Sobieraj, Jacek Wilkosz, Piotr Kania, Adam Jędrzejczyk, Bogdan Kałużewski, Agnieszka Gach, Tadeusz Kałużewski   +12 more
wiley   +1 more source

Modeling Returns Distribution Based upon Radical Normal Distributions

, 2005
The main subject of this paper is to develop a heuristic method to identify returns distribution of an asset or a portfolio more accurately than the well-assumed conventional distributions do, such as, normal, lognormal, or stable distribution. Certainly
譚, 康融, タン, コウユウ, 70368968, 847   +3 more
core  

Mixed normal conditional heteroskedasticity [PDF]

, 2002
Both unconditional mixed-normal distributions and GARCH models with fat-tailed conditional distributions have been employed for modeling financial return data.
Mittnik, Stefan, Haas, Markus, Paolella, Marc S.   +2 more
core  

A novel approach to form Normal Distribution of Medical Image Segmentation based on multiple doctors' annotations. [PDF]

Proc SPIE Int Soc Opt Eng, 2022
Zhou Z, Liao G.
europepmc   +1 more source

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

Molecular Oncology, EarlyView.
This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska, Stephany Gallardo, Nur S. Zainal, Leena Arora, Matthew Ellis, Maria‐Antoinette Lopez, Judith Austine, Sai Pittla, Serena J Chee, Aiman Alzetani, Emily C Shaw, Christian H Ottensmeier, Gareth J Thomas, Christopher J Hanley   +13 more
wiley   +1 more source

Multivariate mixed normal conditional heteroskedasticity [PDF]

We propose a new multivariate volatility model where the conditional distribution of a vector time series is given by a mixture of multivariate normal distributions. Each of these distributions is allowed to have a time-varying covariance matrix.
J.V.K., ROMBOUTS, Luc, BAUWENS, C.M., HAFNER   +2 more
core  

Sparse Representation With Gaussian Atoms and Its Use in Anomaly Detection

IEEE Open Journal of Signal Processing
We propose sparse representation and dictionary learning algorithms for dictionaries whose atoms are characterized by Gaussian probability distributions around some central atoms.
Denis C. Ilie-Ablachim, Andra Baltoiu, Bogdan Dumitrescu   +2 more
doaj   +1 more source