“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...

Although there are many measures of variability for qualitative variables, they are little used in social research, nor are they included in statistical software. The aim of this article is to present ...

Logistic regression is truly no different! It also gives you link-transformed conditional expectation, as any other of the GLM family, here - for the Bernoulli distribution so it has natural ...

particle filtering: bootstrap filter, guided filter, APF. resampling: multinomial, residual, stratified, systematic and SSP. possibility to define state-space models using some (basic) form of ...

Department of Physics, Trinity College, Hartford, USA. Although the SARS-Cov-2 virus presents many biochemical and biophysical mysteries for scientists to research, the question of greatest import for ...

Single-cell RNA sequencing provides high-throughput gene expression information to explore cellular heterogeneity at the individual cell level. A major challenge in characterizing high-throughput gene ...

tascCODA posits a Dirichlet-Multinomial model for Y i,⋅ for each sample i ∈ 1…, n, thus accounting for the compositional nature of the count data. The covariates are associated with the features ...

Count data are ubiquitous in natural sciences 1,2,3,4,5,6,7,8 and other fields 9,10,11,12,13. The default modeling choice for count data has traditionally been a Poisson regression but it is widely ...

Statistical analysis is crucial for research and the choice of analytical technique should take into account the specific distribution of data. Although the data obtained from health, educational, and ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Though MS has always appeared to be quite different from ...