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In our application of the Piot model, selection means that the health professional suspects TB and requests a sputum examination and/or X-ray examination.
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Model selection by means of the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estimation.
The AIC is a tool for model selection, which means it can be used to compare competing models with one another.
Both DIC as a measure of model selection and mean of logarithmic score (LS ¯ (r ), r = 1,…,100) were calculated for all 100 runs.
Each of these criteria ranks the quality of the model fit and thus provides a means for model selection.
AICc is considered to be a simple, effective, and objective means for model selection [20].
Model selection was determined analytically by means of likelihood ratio tests and included random intercepts.
Additional file 1: Description of subcongenic analysis, model selection and estimation of LS Means for each congenic.
We used Akaike's information criterion (AIC) as a means of model selection to determine whether introgression sufficiently explained variation in plant traits compared to abiotic factors from the population origins (Burnham and Anderson 2002).
By means of model selection method such as Akaike Information Criterion (AIC) and statistical assessment like student's t-test [ 25- 27], the significant regulations and interactions between genes and proteins were detected (see Methods).
We now consider the selected graphical model, obtained by means of (backward) model selection from the mixed data source, obtained by averaging the complete variance-covariance matrices of financial and tweet data, as shown in the "Application and results" section.
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