Bayesian nonparametric estimation of the spectral density of a long memory Gaussian time series

However, although reasonably expected, the extension of our results and those of [17] on the classification of transition fronts having a global mean speed, on the clas- sification

Trajectory Tracking Control Design for Large-Scale Linear Dynamical Systems With Applications to Soft Robotics.. IEEE Transactions on Control Systems Technology, Institute of

The association of increased muscle protein catabolism, mitochondrial dysfunction and fatty acid accumulation in skeletal muscle of animals with arthritis supports the hypothesis

Après une relation fusionnelle avec elle, la cadette de la famille a estimé que cela n’est pas suffisant.. Elle veut

The habitat choices are also consistent with life-history differences between peregra and ovata from the stony shore; ovata reproduction was much more negatively affected in

A potentially clinically relevant decrease in faldaprevir exposure was observed when coadministered with efavirenz; this decrease can be managed using the higher of the 2

Several models in the time series literature are defined through their spectral density. By taking k large enough, g may be arbitrarily close to any function in a certain

Rate optimal semiparametric estimation of the memory parameter of the Gaussian time series with long range dependence, Journal of Time Series Analysis 18, 49-61.. [16]