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...
However, practitioners struggle to use explainability methods because they do not know which explanation to choose and how to interpret the explanation. Here we address the challenge of using explainability methods by proposing TalkToModel: an interactive dialogue system that explains ML models through ...
The base model resulted in a linear regression coefficient of 0.4 compared to 0.9 (RMSE = 7 μg/m3) when applying the LMEM using the AOD/CWV ratio in both the random and fixed effects parts of the model. In recent years machine learning has been introduced to the field, mainly for ...
and various molecular structure property prediction methods have been proposed [2,3,4,5]. These methods can be divided into feature-based methods and feature-free methods according to the type of data that are input into the model. Feature-based methods take the generated fixed molecular...
the exchanges of information systems or signal molecules, such as quorum sensing, may mediate species interactions62,63. Since microbial interactions in natural habitats are difficult to reproduce under laboratory conditions, our approach provides insights into observing co-occurrence and interpreting metabol...
effects models (GLMM) with binomial distribution with the “glmer” function (p-value ≤ 0.05) of the “lme4” R package (Bates et al.2015). Model included stem mortality as dependent variable and fire severity (dNBR), species, and their interaction as fixed effects, using the plot ...
Suppose we want to fit a regression model to this data set with fixed parameter \(\varvec{\theta } \in \mathbb {R}^p\), where the adopted model reflects the interesting aspects of the true data-generating process and \(\varvec{\theta }_0\) is the true parameter value. In linear ...
There are two types of meta-CART algorithm: fixed-effect (FE) meta-CART, a partitioning algorithm that ignores the residual heterogeneity unexplained by the moderators, and random-effects (RE) meta-CART, a partitioning algorithm that takes into account the residual heterogeneity. As in standard ...
and interpreting studies. A large experiment that finds an intervention increases scores on, for example, PLATO’s Classroom Discourse dimension would not necessarily have found gains on FFT’s Using Questioning and Discussion Techniques, nor on similar constructs in other rubrics. Unless researchers ...
s quantitative electroencephalogram (qEEG) from nocturnal breathing, which prevents the model from overfitting and helps in interpreting the output of the model. Our system aims to deliver a diagnostic and progression digital biomarker that is objective, nonobtrusive, low-cost and can be measured ...