Resolution:
## Figure 1.
Comparison between simple and adapted maximum likelihood estimation.
Graph A. The upper panel represents a set of 30 covariate pairs (‚samples‘) which can be
described by a linear function. Deviation from this function is due to a simulated
technical error. The lower panel comprises 30 samples for which half of the data were
shifted for a constant value. Graph B Likelihood distribution for the hypotheses space using the simple maximum likelihood
estimator using data from upper and lower panel from graph A. For any given linearity
parameter (slope and intercept), the estimated likelihood is increasing from white
to cyan, blue, gree, yellow, orange and red. Upper panel: For a single linearity,
the global maximum (black circle) matches with the linearity parameters of the simulated
function (green circle). Lower panel: The simple maximum likelihood estimator fails
to detect and represent the presence of two linear functions. The global maximum is
calculated for a single linearity which is depicted in graph A, lower panel. Graph C: Likelihood distribution for the hypotheses space using the simple maximum likelihood
estimator using the same data set as in graphs A and B. A single linearity is correctly
identified (upper panel). Importantly, data sets comprising more than one linear function
are also correctly matched reporting both slope and intercept parameters.
Kose |