As an example we fit the historical data from Figures 2a to (39).
Similar to the Buffalo snowfall example, we fit the GPD model in (4) with MLEs of the parameters, (widehat {sigma }_{MLE}=5.3011), (widehat {gamma }_{MLE}=0.1234,) to the CO2 emission data, which is demonstrated in Fig. 11(a), (b) by the log-log plot and histogram.
Figure 1B displays an example of the model we fit to the probe-level data from a microarray study.
For example, we tried fitting low order polynomials to division rates over time, but the fits were unsatisfactory, as judged by assuming counts were Poisson distributed with rates predicted from the polynomial fit.
For example, we could fit over 900 holes of 1-mm diameter into one 7 cm×3 cm sheet.
For example, we could fit a treatment-by-randomisation period interaction to see whether there is evidence that the treatment effect varies over time.
For those species where we have a significant number of data points (tilapia, M. benetos, M. zebra, L. fuelleborni), we fitted the raw data and plot only the fit curves for clarity (for example, fits from Figures 3 and 4, and Additional file 5; see Additional file 3 for curve fits).
For example, for the hypothesis H3 we fit a GP to the combination of Th0 and Th2 time-course profiles and another GP to the Th1 time-course profiles.
In the next example we illustrate how to fit models with various sets of predictors using the mice data set.
In this example we show how to fit models that induce variable selection and others that shrink estimates toward zero.
