Here we display a simultaneous fit of four source-plus-background ACIS-S/HETG grating spectra, with the source modeled by an absorbed broken power-law, and the background modeled by an absorbed power-law.
To describe the source contributions to the total emission in the spectrum, we define a source model consisting of an absorbed power-law multiplied by an absorbed thermal plasma model, to describe the bright central point source and the surrounding diffuse thermal gas, respectively.
Individuals in every state may die, represented in the model as an absorbing state - death, with a risk that varies with age and time.
Call normal_sample with default settings to return the fit statistic value and model parameter values resulting from the best fit of an absorbed power-law model to default data set 1, where all thawed parameters are considered to be correlated in the fit, and therefore sampled from a multi-variate Gaussian distribution.
Call t_sample with default settings to return the fit statistic value and model parameter values resulting from the best fit of an absorbed power-law model to default data set 1, where all thawed parameters are sampled from the Student's t-distribution.
Call uniform_sample with default settings to return the fit statistic value and model parameter values resulting from the best fit of an absorbed power-law model to default data set 1, where all thawed parameters are sampled from the standard uniform distribution.
The background is subtracted, the analysis restricted to the 0.1 to 6 keV range, a model is created - consisting of an absorbed power law - and then parameter values are set before the fit is made.
Fit an absorbed power-law model to source data set "1", and then run the covariance function to calculate confidence intervals for the thawed parameters.
We fit an absorbed power-law model to the data using the robust, Nelder-Mead Simplex fit optimization method and Cash fit statistic in order to select a Poisson likelihood as appropriate for pyBLoCXS simulations.
Then, we can model the transition process as an absorbing time-homogeneous Markov chain whose state space is (2).
