Recent studies using a novel copying model statistical approach appear to suggest an initial northern and southern origin (Cambodians, Mongolians, Xibo, Yi, Tu, Daur, and Naxi receiving large contributions from central-Asian populations) that contribute to Han ancestry [28].
Furthermore, when used in combination with specific mixed-effects model statistical approaches [ 3- 5], pedigree information allows for the estimation of relevant quantitative genetic parameters, including additive genetic and environmental variances and covariances for traits, as well as their underlying and associated quantitative trait loci (QTL).
Among the three approaches to develop energy models, statistical approaches are a good option to avoid the burden associated to engineering approaches when observed/measured data is available.
The natural experiment research design controls for confounding variables, and our conceptual model and statistical approach integrate natural and social sciences data.
Here we use the Factor Model, a statistical approach recently modified to be used in landmark data, to evaluate original design attributes versus changes attributed to maintenance activities on a sample of Southern Patagonia lithic stemmed points, including arrows and spears.
Due to the non-normality of the data, and the high sensitivity of 0-values in log-linear models, the statistical approach used to analyzing the bioassays was a generalized linear model design with an underlying gamma distribution.
Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach.
This bias is tolerable for the present application, so for simplicity we use Q1 (Additional file 2: Table S1) as a summary statistic uniformly for all samples, without requiring the genotype to be known; we have also developed a mixture-model based statistical approach that aims to mitigate this bias [unpublished observations by Jones et al. 2014].
Despite these caveats, however, the case study approach allows the questions raised earlier on the AoA impact to be discussed in great detail and with a richness that is not possible with either the simulation modelling or statistical approaches.
The few studies that have explored this application have focused on transform, model and statistical approaches.
SARIMA modeling is a statistical approach used to model and forecast nonstationary time series and instances wherein observations are seasonally dependent and autocorrelated (28 ).
