Introducing teachers who use GUI-driven tools for the randomization test to code-driven tools

AIM: We evaluated five stream classification systems observing: 1) differences in richness, abundance and macroinvertebrates communities among stream classes within classification systems; and 2) whether classification systems present better performance using macroinvertebrates. Additionally, we evaluated the effects of taxonomic resolution and data type (abundance and presence) on results. METHODS: Five stream classification systems were used, two based on hydroregions, one based on ecoregions by FEOW, a fourth one based on stream orders and the last one based on clusters of environment variables sampled in 37 streams at Rio Grande do Sul state, Brazil. We used a randomization test to evaluate differences of richness and abundance, a db-MANOVA to evaluate the differences of species assemblages and Classification Strength (CS) to evaluate the classifications performance. RESULTS: There were differences of richness and abundance among stream classes within each stream classification. The same result was found for community data, except for stream order classifications in family level. We observed that stream classes obtained for each stream classification differed in terms of environment variables (db-MANOVA). The classification based on environment variables showed higher CS values than other classification systems. The taxonomic resolution was important to the observed results. Data on genera level presented CS values 12% higher than family level for cluster classification, and the data type was dependent on the classification system and taxonomic resolution employed. CONCLUSION: Our results indicate that classifications based on cluster of environment variables was better than other stream classification systems, and similar results using genera level can be obtained for management programs using family resolution in a geographical context similar to this study.

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2D QSAR Approach to Develop Newer Analogs as Melatonin Receptor Agonist

Dhaka University Journal of Pharmaceutical Sciences ◽

10.3329/dujps.v15i1.29186 ◽

2016 ◽

Vol 15 (1) ◽

pp. 7-19

Author(s):

Supriyo Saha ◽

Mrityunjoy Acharya ◽

Prinsa

Keyword(s):

Mahalanobis Distance ◽

Receptor Agonist ◽

Statistical Parameter ◽

Qsar Model ◽

Randomization Test ◽

Melatonin Receptor ◽

Distance Method ◽

Qsar Analysis ◽

Acceptable Model ◽

Data Points

QSAR analysis was performed using 20 MT1 agonist and 18 MT2 agonist. MODI was 0.6373 in case of MT1 agonist and 0.6299 in case of MT2 agonist. QSAR model for MT1 receptor agonist was pKd = 16.24793(+/- 0.93539) +1.0924(+/-0.18831) ALogP -0.11399(+/-0.01383) apol +0.59876(+/-0.16599) C2SP3 -10.29435(+/-2.81413) E3p and for MT2 receptor agonist was pKd = 6.38692(+/-0.91098) +0.87139(+/-0.20258) ALogP -0.0351(+/-0.00542) AMR +3.33079 (+/-0.80377) SpMin6_Bhm +146.76208(+/-28.14492) VE2_Dt with statistical parameter as Q^2:0.79167, r^2 :0.88878, |r0^2-r'0^2|:0.04633,k:1.03159, [(r^2-r0^2)/r^2]:0.01013, k':0.96695, [(r^2- '0^2)/r^2]:0.06226 and Q^2:0.81401, r^2:0.97384, |r0^2-r'0^2|:0.1039, k:0.98543, [(r^2-r0^2)/r^2]:0.08048, k':1.01351, [(r^2-r'0^2)/r^2]:0.18717 respectively; comply with the Golbraikh and Tropsha acceptable model criteria. The results from MLR Y Randomization test in case of MT1 agonist was cRp^2: 0.7665 and MT2 agonist was cRp^2: 0.7284. Applicability domain were identified by Euclidean and Mahalanobis Distance Method. Finally it was clear that all the predicted data are inside the area of observed data points and also some data are purely overlapped.Dhaka Univ. J. Pharm. Sci. 15(1): 7-19, 2016 (June)

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Panel experiments and dynamic causal effects: A finite population perspective

Quantitative Economics ◽

10.3982/qe1744 ◽

2021 ◽

Vol 12 (4) ◽

pp. 1171-1196 ◽

Cited By ~ 1

Author(s):

Iavor Bojinov ◽

Ashesh Rambachan ◽

Neil Shephard

Keyword(s):

Fixed Effects ◽

Serial Correlation ◽

Finite Population ◽

Relative Effectiveness ◽

Randomization Test ◽

Causal Effects ◽

Probability Limit ◽

Population Probability ◽

Potential Outcomes Framework ◽

Randomization Distribution

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative treatment paths. For a rich class of dynamic causal effects, we provide a nonparametric estimator that is unbiased over the randomization distribution and derive its finite population limiting distribution as either the sample size or the duration of the experiment increases. We develop two methods for inference: a conservative test for weak null hypotheses and an exact randomization test for sharp null hypotheses. We further analyze the finite population probability limit of linear fixed effects estimators. These commonly‐used estimators do not recover a causally interpretable estimand if there are dynamic causal effects and serial correlation in the assignments, highlighting the value of our proposed estimator.

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Asymptotic Behavior of a Randomization Test for a Response-Adaptive Design

Sequential Analysis ◽

10.1080/07474946.2015.995979 ◽

2015 ◽

Vol 34 (1) ◽

pp. 39-56

Author(s):

Arkaitz Galbete ◽

José A. Moler ◽

Fernando Plo

Keyword(s):

Asymptotic Behavior ◽

Adaptive Design ◽

Randomization Test

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The Performance of the Date-Randomization Test in Phylogenetic Analyses of Time-Structured Virus Data

Molecular Biology and Evolution ◽

10.1093/molbev/msv056 ◽

2015 ◽

Vol 32 (7) ◽

pp. 1895-1906 ◽

Cited By ~ 93

Author(s):

Sebastián Duchêne ◽

David Duchêne ◽

Edward C. Holmes ◽

Simon Y.W. Ho

Keyword(s):

Phylogenetic Analyses ◽

Randomization Test

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Waiting to make an impact: a probable excess of near-Earth asteroids in 2018 LA-like orbits

Astronomy and Astrophysics ◽

10.1051/0004-6361/201834313 ◽

2019 ◽

Vol 621 ◽

pp. A137

Author(s):

C. de la Fuente Marcos ◽

R. de la Fuente Marcos

Keyword(s):

Outer Space ◽

Statistical Significance ◽

Randomization Test ◽

Orbital Evolution ◽

Parent Body ◽

Meteor Shower ◽

Physical Relationship ◽

Common Precursor ◽

Near Earth Asteroids ◽

Orbit Model

Context. The discovery and tracking of 2018 LA marks only the third instance in history that the parent body of a fireball has been identified before its eventual disintegration in our atmosphere. The subsequent recovery of meteorites from 2018 LA was only the second time materials from outer space that reached the ground could be linked with certitude to a particular minor body. However, meteoroids like 2018 LA and its forerunners, 2008 TC3 and 2014 AA, are perhaps fragments of larger members of the near-Earth object (NEO) population. As the processes leading to the production of such fragments are unlikely to spawn just one meteoroid per event, it is important to identify putative siblings and plausible candidates from which the observed meteoroids might have originated. Aims. Here, we study the pre-impact orbital evolution of 2018 LA to place this meteoroid within the dynamical context of other NEOs that follow similar trajectories. Methods. Our statistical analyses are based on the results of direct N-body calculations that use the latest orbit determinations and include perturbations by the eight major planets, the Moon, the barycentre of the Pluto–Charon system, and the three largest asteroids. A state-of-the-art NEO orbit model was used to interpret our findings and a randomization test was applied to estimate their statistical significance. Results. We find a statistically significant excess of NEOs in 2018 LA-like orbits; among these objects, we find one impactor, 2018 LA, and the fourth closest known passer-by, 2018 UA. A possible connection with the χ-Scorpiids meteor shower is also discussed. The largest known NEO with an orbit similar to that of 2018 LA is the potentially hazardous asteroid (454100) 2013 BO73 and we speculate that they both originate from a common precursor via a collisional cascade. Conclusions. Future spectroscopic observations of 454100 and other NEOs in similar orbits may confirm or deny a possible physical relationship with 2018 LA.

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Chemometric Modeling of the Ecotoxicity of Industrial Chemicals to an Avian Species Anas Platyrhynchos

International Journal of Quantitative Structure-Property Relationships ◽

10.4018/ijqspr.2020040101 ◽

2020 ◽

Vol 5 (2) ◽

pp. 1-16

Author(s):

Shinjita Ghosh ◽

Supratik Kar ◽

Jerzy Leszczynski

Keyword(s):

Anas Platyrhynchos ◽

External Validation ◽

Quantitative Structure Activity Relationship ◽

Randomization Test ◽

Avian Species ◽

Industrial Chemicals ◽

Linear Discriminant ◽

Topological Distance ◽

Qsar Models ◽

Classification And Regression

Birds or avians have been imperative species in the ecology, having been evaluated in an effort to understand the toxic effects of endocrine disruption. The ecotoxicity of 56 industrial chemicals classified as endocrine disruptors were modeled employing classification and regression-based quantitative structure-activity relationship (QSAR) models to an important avian species, Anas platyrhynchos. The classification- and regression-based QSAR models were developed using linear discriminant analysis (LDA) and partial least squares (PLS) tools, respectively. All models were validated meticulously by employing internal and external validation metrics followed by randomization test, applicability domain (AD) study, and intelligent consensus prediction of all individual models. Features like topological distance of 1, 3, and 5 between atoms O-P, C-P, and N-S, correspondingly, along with the CR3X fragment, can be responsible for an increase in toxicity. On the contrary, the presence of S-Cl with topological distance 6 is accountable for lowering the toxicity of towards A. platyrhynchos. The developed chemometric models can offer significant evidence and guidance in the framework of virtual screening as well as a toxicity prediction of new and/or untested chemical libraries towards this specific avian species.

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