Results 21 to 30 of about 1,926,955 (188)

Sensor-AssistedWeighted Average Ensemble Model for Detecting Major Depressive Disorder [PDF]

, 2019
The present methods of diagnosing depression are entirely dependent on self-report ratings or clinical interviews. Those traditional methods are subjective, where the individual may or may not be answering genuinely to questions.
Chang, Chuan-Yu, Gao, Liang, Garg, Akhil, Gutiérrez Reina, Daniel, Mahendran, Nivedhitha, Srinivasan, Kathiravan, Vincent, Durai Raj   +6 more
core   +1 more source

Use of Principal Component Analysis to Combine Genetic Merit for Heat Stress and for Fat and Protein Yield in Spanish Autochthonous Dairy Goat Breeds

Animals, 2021
We studied the effect of the Temperature Humidity Index (THI) (i.e., the average of temperature and relative humidity registered at meteorological stations) closest to the farms taken during the test day (TD), for total daily protein and fat yields (fpy)
Alberto Menéndez-Buxadera, Eva Muñoz-Mejías, Manuel Sánchez, Juan Manuel Serradilla, Antonio Molina   +4 more
doaj   +1 more source

Variable Selection and Model Choice in Geoadditive Regression Models [PDF]

, 2007
Model choice and variable selection are issues of major concern in practical regression analyses. We propose a boosting procedure that facilitates both tasks in a class of complex geoadditive regression models comprising spatial effects, nonparametric ...
Hothorn, Torsten, Kneib, Thomas, Tutz, Gerhard   +2 more
core   +1 more source

Random Regression Analysis of Calving Interval of Japanese Black Cows

Animals, 2021
We estimated genetic parameters for the calving interval of Japanese Black cows using a random regression model and a repeatability model. We analyzed 92,019 calving interval records of 36,178 cows. Pedigree data covered 390,263 individuals.
Shinichiro Ogawa, Masahiro Satoh
doaj   +1 more source

A generalized linear mixed model for longitudinal binary data with a marginal logit link function [PDF]

, 2011
Longitudinal studies of a binary outcome are common in the health, social, and behavioral sciences. In general, a feature of random effects logistic regression models for longitudinal binary data is that the marginal functional form, when integrated over
Fitzmaurice, Garrett M., Ghosh, Souparno, Ibrahim, Joseph G., Lipsitz, Stuart, Mallick, Bani K., Parzen, Michael, Sinha, Debajyoti   +6 more
core   +3 more sources

Estimation of the Breeding Values and Genetic Parameters in Teleorman Black Head Sheep Breed

Scientific Papers Animal Science and Biotechnologies, 2023
The aim of this paper was to study the breeding values and genetic parameters estimation methodology applied on Teleorman Black Head Sheep breed genetic improvement programs.
Florin Popa, Horia Grosu, Mircea Catalin Rotar, Rodica Stefania Pelmus, Mihail Alexandru Gras, Cristina Lazar   +5 more
doaj  

Persistence in milk, fat and protein production of primiparous Holstein cows by random regression models Persistence in milk, fat and protein production of primiparous Holstein cows by random regression models

Revista Brasileira de Zootecnia, 2010
Total numbers of 56,508, 35,091 and 8,326 records of milk, fat, and protein test-day yields, respectively, were used to estimate genetic parameters for six persistency measures on milk, fat and protein productions of Holstein cows reared in Minas Gerais ...
Igor de Oliveira Biassus, Jaime Araújo Cobuci, Claudio Napolis Costa, Paulo Roberto Nogara Rorato, José Braccini Neto, Leandro Lunardini Cardoso   +5 more
doaj   +1 more source

GENETIC PARAMETERS FOR GROWTH PERFORMANCE TRAITS OF EGYPTIAN BARKI LAMBS USING RANDOM REGRESSION MODEL [PDF]

Arab Universities Journal of Agricultural Sciences, 2019
Variance components and genetic parameters for growth traits were estimated for Barki lambs using the average information REMLF90 (AIREMLF90). A total of 3205 Barki lambs’ records over the period from 1984 to 2017 from experimental Borg Al-Arab station ...
Sh. Melak, H. Mansour, A. Aboul-Naga, Mona Osman, A. Elbeltagy, Manal El Sayed   +5 more
doaj   +1 more source

Bagging ensemble selection for regression [PDF]

, 2012
Bagging ensemble selection (BES) is a relatively new ensemble learning strategy. The strategy can be seen as an ensemble of the ensemble selection from libraries of models (ES) strategy. Previous experimental results on binary classification problems have
D.H. Wolpert, E. Bauer, J. Demšar, J.H. Friedman, J.H. Friedman, L. Breiman, L. Rokach, Q. Sun, R. Bryll, Z.-H. Zhou, Z.H. Zhou   +10 more
core   +1 more source

Finite mixture regression: A sparse variable selection by model selection for clustering [PDF]

, 2014
We consider a finite mixture of Gaussian regression model for high- dimensional data, where the number of covariates may be much larger than the sample size. We propose to estimate the unknown conditional mixture density by a maximum likelihood estimator,
Devijver, Emilie
core   +4 more sources