doi:10.2139/ssrn.3699777research methodseconometricsfixed effectsfinancial economicsaccountingFixed effects are ubiquitous in financial economics studies, but many researchers have a limited understanding of how they function. This manuscript explains hoSocial Science Electronic Publishing...
Using and Interpreting Fixed Effects Models 来自 SSRN 喜欢 0 阅读量: 732 摘要: Fixed effects are ubiquitous in financial economics studies, but many researchers have a limited understanding of how they function. This manuscript explains ho 关键词: research methods econometrics fixed effects financial...
The functional response of a plant community to a wildfire can be used to study the response to the new environment and to the disturbance across taxa (Donato et al.2009). Traits related to regeneration strategies (i.e., seed longevity, germination, growth form) and competition (i.e., gro...
interactions by the RMT threshold were ET: 716 Kbp, HT: 1204 Kbp, and MT: 879 Kbp. However, the average genome size differences for mutualistic interactions were close to 0 for all three temperature groups. In all commensalistic interactions, the proportion of interactions where the esti...
LQMM allows for the inclusion of both random effects and fixed effects in the model, serving as an extension of both quantile regression (QR) and linear mixed models. LQMM offers flexibility in investigating the effects of covariates on the entire conditional distribution of the response, while ...
allometry relationships established for all species depend on the phylogenetic correlations (this is because fixed effects depends on random effects and vice versa), and species-level predictions remain influenced by the specificities of the species that correlate with the phylogeny....
1, we use the feature-sets extracted on its training set and evaluate the models using leave-one-subject-out cross validation on the test set. Each experiment is repeated 25 times to capture variability. For the binary classifiers—SSVM and linear SVM—we used a multiclass method, with ...
and PCR artifacts as well as reagent contaminants [3,11]. A notable exception is count tables generated using feature inference methods, such as DADA2 [8]. Sequence inference methods aim to reduce the number of features from sequence artifacts by using statistical models to group sequences by ...
To address this challenge, we analyzed the NN activity by clustering the neural activation values in the hidden layers, to obtain clusters with similar activation patterns (Interpreting and analyzing the deep-RL agents in Methods section). We analyzed a nominal agent that was trained in a range ...
PRnet outperformed alternative models in the “R2 in the compound” and “R2 in cov_compound” metrics in unseen compounds (R2 in the compound: 0.969) and unseen pathways scenarios (R2 in the compound: 0.97) than the other methods. The low-dimensional (t-SNE) representation ...