Results 131 to 140 of about 1,223,755 (370)

A Novel Location Method for Multi-Target Based on the Maximum Likelihood Estimation [PDF]

, 2016
Ma Xian-tong, Jingqing Luo
openalex   +1 more source

Insights Into the Antigenic Repertoire of Unclassified Synaptic Antibodies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective We sought to characterize the sixth most common finding in our neuroimmunological laboratory practice (tissue assay‐observed unclassified neural antibodies [UNAs]), combining protein microarray and phage immunoprecipitation sequencing (PhIP‐Seq). Methods Patient specimens (258; 133 serums; 125 CSF) meeting UNA criteria were profiled;
Michael Gilligan, John R. Mills, Paulina Vargas, Naveen K. Paramasivan, Connie E. Lesnick, Eati Basal, Surendra Dasari, James P. Fryer, Shannon R. Hinson, Joseph Laporta, Amy Espinal, Dennis Fitzgerald, Carolina Garcia, Anna E. Morenkova, Paola Pergami, Anna Shah, Andrew Knight, Reghann LaFrance Corey, Vanda A. Lennon, Anastasia Zekeridou, Sean J. Pittock, Divyanshu Dubey, Andrew McKeon   +22 more
wiley   +1 more source

Maximum Likelihood Estimation in Mixed Integer Linear Models. [PDF]

IEEE Signal Process Lett, 2023
Tucker D, Zhao S, Potter LC.
europepmc   +1 more source

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

CherryML: scalable maximum likelihood estimation of phylogenetic models. [PDF]

Nat Methods, 2023
Prillo S, Deng Y, Boyeau P, Li X, Chen PY, Song YS.   +5 more
europepmc   +1 more source

Nonparametric maximum likelihood estimation of probability densities by penalty function methods [PDF]

When it is known a priori exactly to which finite dimensional manifold the probability density function gives rise to a set of samples, the parametric maximum likelihood estimation procedure leads to poor estimates and is unstable; while the ...
Demontricher, G. F., Tapia, R. A., Thompson, J. R.   +2 more
core   +1 more source

Frailty Exacerbates Disability in Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background To evaluate frailty in severe progressive multiple sclerosis (PMS) and to investigate the underlying mechanisms. Methods This prospective, cross‐sectional, multicenter study enrolled a late severe PMS group requiring skilled nursing (n = 53) and an age, sex, and disease duration‐matched control PMS group (n = 53).
Taylor R. Wicks, Anna Wolska, Diala Ghazal, Dejan Jakimovski, Bianca Weinstock‐Guttman, Alexander Burnham, Niels Bergsland, Michael G. Dwyer, Alan T. Remaley, Robert Zivadinov, Murali Ramanathan   +10 more
wiley   +1 more source

Maximum Likelihood Estimation of Hierarchical Linear Models from Incomplete Data: Random Coefficients, Statistical Interactions, and Measurement Error

, 2023
Yongyun Shin, Stephen W. Raudenbush
openalex   +1 more source

Scenario Generations for Renewable Energy Sources and Loads Based on Implicit Maximum Likelihood Estimations [PDF]

, 2022
Wenlong Liao, Birgitte Bak‐Jensen, Jayakrishnan Radhakrishna Pillai, Zhe Yang, Yusen Wang, Kuangpu Liu   +5 more
openalex   +1 more source

MAXIMUM LIKELIHOOD ESTIMATION AND INFERENCE ON COINTEGRATION — WITH APPLICATIONS TO THE DEMAND FOR MONEY

, 2009
S. Johansen, K. Juselius
semanticscholar   +1 more source