Results 111 to 120 of about 4,929,720 (302)

Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors [PDF]

open access: yes
We consider nonparametric estimation of the conditional qth quantile for stationary time series. We deal with stationary time series with strong time dependence and heavy tails under the setting of random design.
Toshio Honda
core  

Random effect regression model.

open access: yes, 2020
Random effect regression model.
Yuewen Jiang (8356740)   +4 more
core   +1 more source

The impact of leukocyte‐associated RNA retention on platelet RNA‐based cancer detection

open access: yesMolecular Oncology, EarlyView.
Platelets carry RNA signals that may help detect cancer, but platelet samples can also retain RNA from white blood cells. We found that this retained white blood cell signal did not significantly affect machine learning cancer classification, suggesting that the cancer‐related RNA signal in platelets is largely independent of leukocyte‐associated RNA ...
Michał Sieczczyński   +12 more
wiley   +1 more source

Uso de modelos de regressão aleatória para descrever a variação genética da produção de leite na raça Holandesa Random regressions models to describe the genetic variation of milk yield in Holstein breed

open access: yesRevista Brasileira de Zootecnia, 2006
Registros de produção de leite de 68.523 controles leiteiros de 8.536 vacas da raça Holandesa, com parições nos anos de 1996 a 2001, foram utilizados na comparação entre modelos de regressão aleatória para estimação de componentes de variância.
Cláudio Vieira de Araújo   +8 more
doaj   +1 more source

Random-effects logistic regression analysis for association between cluster membership and testing seropositive for pig zoonoses.

open access: yes, 2016
Random-effects logistic regression analysis for association between cluster membership and testing seropositive for pig zoonoses.
Peter A. Durr (830162)   +15 more
core   +1 more source

RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells

open access: yesFEBS Open Bio, EarlyView.
RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour   +2 more
wiley   +1 more source

Random Forest Regression May Become the Optimal Regression Model for Osteoarthritis of the Knee in Elderly, in the Context of Embodied Cognition and Psychosomatic Medicine

open access: yesJournal of Multidisciplinary Healthcare
Guangyuan Ma,1,* Junjie Chen,2,3,* Jingchi Li,2,3 Hui Shi,1 Yi Chen1 1School of Humanities and Management, Southwest Medical University, Luzhou, Sichuan, People’s Republic of China; 2Department of Orthopedics, The Affiliated Traditional ...
Ma G, Chen J, Li J, Shi H, Chen Y
doaj  

Uso de funções de covariância na descrição do crescimento de bovinos Nelore criados no estado de Pernambuco Use of covariance functions to describe the growth curve of Nelore cattle, in Pernambuco State, Northeastern Brazil

open access: yesRevista Brasileira de Zootecnia, 2005
Este trabalho foi realizado com os objetivos de avaliar diferentes modelos de regressão aleatória, compostos por polinômios de Legendre, utilizados na descrição de efeitos genéticos e ambientais sobre observações do tipo peso-idade e identificar o mais ...
Kleber Régis Santoro   +3 more
doaj   +1 more source

Spurious regression under broken trend stationarity [PDF]

open access: yes
We study the phenomenon of spurious regression between two random variables when the generating mechanism for individual series follows a stationary process around a trend with (possibly) multiple breaks in its level and slope.
Daniel Ventosa-Santaularia   +1 more
core  

Directed evolution of enzymes at the crossroads of tradition and innovation

open access: yesFEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova   +2 more
wiley   +1 more source

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