Data Sparseness and Variance in Accounting Profitability [PDF]
Organizational Research Methods, 2015 A central question in strategic management is why some firms perform better than others. One approach to addressing this question empirically is to decompose the variance in firm-level profitability into firm, industry, location, and year components.
Spyridon Stavropoulos +2 more
semanticscholar +12 more sources
Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection [PDF]
Frontiers in Genetics, 2019 The implementation of genomic selection in recurrent breeding programs raises the concern that a higher inbreeding rate could compromise the long-term genetic gain.
Antoine Allier +5 more
doaj +3 more sources
Accounting for item variance in large-scale databases [PDF]
Frontiers in Psychology, 2010 The Dutch Lexicon Project (DLP, Keuleers et al., 2010) is the third published database providing lexical decision times for a large number of items (after the ELP, Balota et al., 2007, and the FLP, Ferrand et al., 2010). In this commentary, we address the issue of the amount of item variance that models should really try to account for in the DLP ...
Arnaud eRey, Pierre eCourrieu
doaj +6 more sources
ACCOUNTING FOR VARIANCE IN HYPERSPECTRAL DATA COMING FROM LIMITATIONS OF THE IMAGING SYSTEM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Over the course of the past few years, a number of methods was developed to incorporate hyperspectral imaging specifics into generic data mining techniques, traditionally used for hyperspectral data processing.
B. Shurygin +4 more
doaj +5 more sources
Aggression, self-control, life satisfaction, and resilience as predictors of mental health in Brazilian jiu-jitsu athletes [PDF]
Frontiers in Sports and Active LivingIntroductionBrazilian jiu-jitsu has been discussed as an effective type of psychosocial therapy, with the social interactions within the Brazilian jiu-jitsu community serving as a buffer against mental health disorders.
Leandro de Lorenco-Lima +2 more
doaj +2 more sources
Uncovering hidden variance: pair-wise SNP analysis accounts for additional variance in nicotine dependence [PDF]
Human Genetics, 2010 Results from genome-wide association studies of complex traits account for only a modest proportion of the trait variance predicted to be due to genetics. We hypothesize that joint analysis of polymorphisms may account for more variance. We evaluated this hypothesis on a case-control smoking phenotype by examining pairs of nicotinic receptor single ...
Robert Culverhouse +9 more
openalex +4 more sources
Accounting for heterogeneity in the variance of unobserved effects in mixed logit models [PDF]
Transportation Research Part B: Methodological, 2006 The growing popularity of mixed logit to obtain estimates of willingness to pay (WTP) has focussed on the distribution of the random parameters and the possibility of estimating deep parameters to account for heterogeneity around the mean of the distribution.
W. Greene, D. Hensher, J. Rose
semanticscholar +3 more sources
An update on modeling dose–response relationships: Accounting for correlated data structure and heterogeneous error variance in linear and nonlinear mixed models1,2 [PDF]
Journal of Animal Science, 2016 Márcio Gonçalves +6 more
openalex +2 more sources
Accounting for Heterogeneous Variances in Multitrait Evaluation of Jersey Type Traits [PDF]
Journal of Dairy Science, 2006 The multitrait genetic evaluation system for type traits was modified to estimate adjustments for heterogeneous variance (HV) simultaneously with estimated breeding values (EBV) for final score and 14 linear traits. Each variance within herd, year, and parity was regressed toward a predicted variance, which was determined by fitting a model with fixed ...
Nicolas Gengler +4 more
openalex +6 more sources
Accounting for variance and hyperparameter optimization in machine learning benchmarks
, 2022 The recent revolution in machine learning has been strongly based on the use of standardized benchmarks. Providing clear target metrics and undeniable measures of improvements of learning algorithms, they are at the center of the scientific methodology in machine learning.
Bouthillier, Xavier
openalex +2 more sources