We monitored shrub recruitment and cover during nine postfire years in northwestern Patagonia grasslands and we studied the long-term population dynamics under different environmental conditions through a matrix model, exploring different fire frequencies and spring precipitation regimes.
Once the predictive or confounder covariates were determined, they were used in subsequent models exploring different averaging periods or alternative pollutant mixes (i.e., BaP equivalents or carcinogenic PAHs).
The HMM model only explores different temporal patterns of DE/EE states and does not rank the genes by statistical significance, but is classifying gene expression profile into a number of temporal patterns by posterior distribution of latent states.
In the second wave model we explored different combinations of drug treatment rates and vaccination uptake on the level of infection, including the effects of prior immunity from the first wave.
Logistic regression was used in multivariate models to explore different variables' impact on the MSI-status and the number of examined lymph nodes.
The simulation model proposed allows exploring different alternatives of wiring modules and finding the most efficient configurations for photovoltaic plants of medium and high power.
In our case, it allows researchers, for example, to explore different nonlinear models without interfering the other parts of the algorithm.
The model explores the likelihood of different outcomes from an investment, including an expected return multiple (ERM), essentially the value of the investment.
When we explored different model forms using generalized additive mixed models for the two ocean basins, we found that a linear model was sufficient for the Caribbean (Fig. S5A), but a non-linear changepoint or breakpoint model [21] was needed for the Indo-Pacific (Fig. S5B).
This finding emphasizes the importance of exploring different models (in conjunction with model validation) to understand brain mechanisms that support cognitive operations.
