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Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by using Bayesian inference and estimating a joint probability distribution over the variables for each timeframe. Kálmán, one of the primary developers of its theory.

The Kalman filter has numerous applications in technology.

Your bug reports and comments are important to keep this library alive. didn't like the use of old strstream header, so I had to add some conditional code for the library to compile both on GCC 4. If someone out there tries to compile on one of those compilers, I would be glad to hear about it.

Thanks for the bug report that allowed this important new release.

The test is a Wald test on the augmented model, which replaces the original as the "current model" for the purposes of, for example, retrieving the residuals as option (available only for the models estimated via OLS), an LM test is performed.

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Menu path: Model window, /Tests/Add variables command with regular time series data.is a library implementing an Extended Kalman Filter in C . Subclassing allows to define different matrix contents for the filter to work with.Kalman filters are used for some time now, in aeronautics, robot vision and robotics in general.This library makes heavy use of the excellent Eigen3 library for linear algebra operations and is thus a required dependency.In order to use the library to do state estimation, a number of things have to be done: template type as your vector or derive your own specialized state vector from that.

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