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3. Similarity-Based Predictive Models: Sensitivity Analysis and a Biological ...
4 jul 2023 · ... (d) model M2 and Euclidean distance. In summary, the empirical similarity models (M1 and M2) and the linear regression model demonstrate ...
Predictive models based on empirical similarity are instrumental in biology and data science, where the premise is to measure the likeness of one observation with others in the same dataset. Biological datasets often encompass data that can be categorized. When using empirical similarity-based predictive models, two strategies for handling categorical covariates exist. The first strategy retains categorical covariates in their original form, applying distance measures and allocating weights to each covariate. In contrast, the second strategy creates binary variables, representing each variable level independently, and computes similarity measures solely through the Euclidean distance. This study performs a sensitivity analysis of these two strategies using computational simulations, and applies the results to a biological context. We use a linear regression model as a reference point, and consider two methods for estimating the model parameters, alongside exponential and fractional inverse similarity functions. The sensitivity is evaluated by determining the coefficient of variation of the parameter estimators across the three models as a measure of relative variability. Our results suggest that the first strategy excels over the second one in effectively dealing with categorical variables, and offers greater parsimony due to the use of fewer parameters.
4. [PDF] Modeling and scheduling of production systems by using max ...
6 mrt 2023 · for D, model M2. This system consists of two processing stages D and E. For the stages, there are two different units, out of which unit 1 ...
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6. Post-salt carbonates control salt-tectonic minibasin formation
17 nov 2023 · (D) Model M2, without post-salt carbonates and without minibasins. VE—vertical exaggeration. Figure 2. (A–C) Model M1, showing end of salt ...
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7. Impact of Debt Financing on Financial Leverage Risk of Firms
d. Model M2 (FLR-MAD). Coefficients of model M2 (FLR-MAD) is as follows: Table 3 : Coefficient table M1 [Dependent Variable: 2nd difference of FLR (CV)].
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8. [PDF] Bayesian test of significance for conditional independence - arXiv
16 jun 2013 · (d) Model M2 (for X = 2). Z = 1. Z = 2. Z = 3. Y = 1. 77. 85. 248. 410. Y = 2. 165. 135. 120. 420. Y = 3. 188. 21. 24. 233. 430. 241. 392. 1036.
9. Predictive Modeling of the Uniaxial Compressive Strength of Rocks ...
29 mrt 2023 · (b) The variation in error between the measured and predicted values. (c) Error histogram for the training data and (d) model M2 results ...
Sedimentary rocks provide information on previous environments on the surface of the Earth. As a result, they are the principal narrators of the former climate, life, and important events on the surface of the Earth. The complexity and cost of direct destructive laboratory tests adversely affect the data scarcity problem, making the development of intelligent indirect methods an integral step in attempts to address the problem faced by rock engineering projects. This study established an artificial neural network (ANN) approach to predict the uniaxial compressive strength (UCS) in MPa of sedimentary rocks using different input parameters; i.e., dry density (ρd) in g/cm3, Brazilian tensile strength (BTS) in MPa, and wet density (ρwet) in g/cm3. The developed ANN models, M1, M2, and M3, were divided as follows: the overall dataset, 70% training dataset and 30% testing dataset, and 60% training dataset and 40% testing dataset, respectively. In addition, multiple linear regression (MLR) was performed for comparison to the proposed ANN models to verify the accuracy of the predicted values. The performance indices were also calculated by estimating the established models. The predictive performance of the M2 ANN model in terms of the coefficient of determination (R2), root mean squared error (RMSE), variance accounts for (VAF), and a20-index was 0.831, 0.27672, 0.92, and 0.80, respectively, in the testing dataset, revealing ideal results, thus it was proposed as the best-fit predic...
10. Sensitivity of Above-Ground Biomass Estimates to Height-Diameter ...
... D model (M2) as: (4). Next, between-plot variability was accounted for by adding plot random effects (aj,bj) as an additional term in a mixed-effects model ...
It has been suggested that above-ground biomass (AGB) inventories should include tree height (H), in addition to diameter (D). As H is a difficult variable to measure, H-D models are commonly used to predict H. We tested a number of approaches for H-D modelling, including additive terms which increased the complexity of the model, and observed how differences in tree-level predictions of H propagated to plot-level AGB estimations. We were especially interested in detecting whether the choice of method can lead to bias. The compared approaches listed in the order of increasing complexity were: (B0) AGB estimations from D-only; (B1) involving also H obtained from a fixed-effects H-D model; (B2) involving also species; (B3) including also between-plot variability as random effects; and (B4) involving multilevel nested random effects for grouping plots in clusters. In light of the results, the modelling approach affected the AGB estimation significantly in some cases, although differences were negligible for some of the alternatives. The most important differences were found between including H or not in the AGB estimation. We observed that AGB predictions without H information were very sensitive to the environmental stress parameter (E), which can induce a critical bias. Regarding the H-D modelling, the most relevant effect was found when species was included as an additive term. We presented a two-step methodology, which succeeded in identifying the species for which the gener...
11. Estimation of exposure to atmospheric pollutants during pregnancy ... - NCBI
3 mrt 2016 · ... D: model M2 (Dispersion-based static outdoor model); E and F: model M3 (Dynamic outdoor model with raw GPS data) exposure estimates. Each ...
Studies of air pollution effects during pregnancy generally only consider exposure in the outdoor air at the home address. We aimed to compare exposure models differing in their ability to account for the spatial resolution of pollutants, space-time activity ...
12. BMW 2 Series Coupe and Convertible Come Alive in First Spy Video
21 feb 2013 · ... d model, M2 be a 4cyl with more power...sounds very silly. And just imagine this...tune an M235i with a Piggyback and it'll rape the doors ...
BMW 2 Series Coupe and Convertible Come Alive in First Spy Video
13. [PDF] Bayesian Test of Significance for Conditional Independence
7 mrt 2014 · ... d (Model M2). The e-values supporting the hypothesis of conditional independence for both models are given below. Page 17. Entropy 2014, 16.
