Perform maximum likelihood model fitting.
This tool performs a maximum likelihood fitting of a model to unbinned or binned data. All model parameters marked with the attribute free="1" in the input model XML file will be adjusted to the value that maximises the probability that the observed data have been drawn from the model. The tool can mix the analysis of unbinned and binned data, and is also able to perform a joint maximum likelihood analysis of data collected in separate observations or with different instruments.
ctlike will automatically switch between unbinned, binned and joint analysis on basis of the file provided on input (parameter inobs). Providing an event list will lead to an unbinned analysis while providing a counts cube will lead to a binned analysis. If several observations have been stacked into a single counts cube, an exposure cube, a point spread function cube and a background cube need also to be provided. ctlike will automatically prompt for these parameters in case that a counts cube is given. Answering NONE will ignore the exposure cube, point spread function cube and background cube and handle the data as a single observation using the specified instrument response function (parameters caldb and irf).
Multiple observations, including data collected with different instruments, can be handled by specifying an observation definition file on input. Each of the observations will be kept separately and associated with its appropriate instrument response functions, as opposed to a stacked analysis where average response functions, computed using ctexpcube, ctpsfcube and ctbkgcube, are used. If an observation definition file is provided, ctlike will use the joint likelihood of all the observations for parameter optimisation.
By default, ctlike will use the Poisson statistics for likelihood computation, but for binned analysis also Gaussian statistics can be specified (parameter stat). Optionally, a refit can be requested after an initial fit (parameter refit), but normally this is not needed. For all model components that have the tscalc="1" attribute set, ctlike will also compute the Test Statistics value that is a measure of the source significance. Optionally, the spatial model parameters can be kept fixed during that computation (parameter fix_spat_for_ts).
ctlike generates an output model XML file that contains the values of the best fitting model parameters. For all free parameters, an error attribute is added that provides the statistical uncertainty in the parameter estimate. If computation of the Test Statistics has been requested for a model component, a ts attribute providing the Test Statistics value is added. The output model can be used as an input model for other ctools.
chatter = 0: no information will be logged
chatter = 1: only errors will be logged
chatter = 2: errors and actions will be logged
chatter = 3: report about the task execution
chatter = 4: detailed report about the task execution
