Kalman: Forecasts and interpolations for ALMA calibrator variability

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Ada Coda
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Kalman: Forecasts and interpolations for ALMA calibrator variability

Post by Ada Coda » Sun Jun 30, 2019 3:19 am

Kalman: Forecasts and interpolations for ALMA calibrator variability

Abstract: Kalman models an inhomogeneous time series of measurements at different frequencies as noisy sampling from a finite mixture of Gaussian Ornstein-Uhlenbeck processes to try to reproduce the variability of the fluxes and of the spectral indices of the quasars used as calibrators in the Atacama Large Millimeter/Sub-millimeter Array (ALMA), assuming sensible parameters are provided to the model (obtained, for example, from maximum likelihood estimation). One routine in the Kalman Perl module calculates best forecast estimations based on a state space representation of the stochastic model using Kalman recursions, and another routine calculates the smoothed estimation (or interpolations) of the measurements and of the state space also using Kalman recursions. The code does not include optimization routines to calculate best fit parameters for the stochastic processes.

Credit: Guzman, A. E.

Site: http://ascl.net/assets/codes/kalman/kalman.zip
https://ui.adsabs.harvard.edu/abs/2019PASP..131i4504G

Bibcode: 2019ascl.soft06005G

ID: ascl:1906.005
Last edited by Ada Coda on Thu Aug 22, 2019 1:37 pm, edited 1 time in total.
Reason: Updated code entry.

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