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Detection of nonconstant long memory parameter

Lavancier, Frédéric; Leipus, Remigijus; Philippe, Anne; … - In: Econometric theory 29 (2013) 5, pp. 1009-1056

Persistent link: https://www.econbiz.de/10010248314

Estimating Long Memory in Panel Random‐Coefficient AR(1) Data

Leipus, Remigijus; Philippe, Anne; Pilipauskaitė, Vytautė - In: Journal of Time Series Analysis 41 (2020) 4, pp. 520-535

Persistent link: https://www.econbiz.de/10012192371

Spatial birth–death–move processes : Basic properties and estimation of their intensity functions

Lavancier, Frédéric; Le Guével, Ronan - In: Journal of the Royal Statistical Society: Series B … 83 (2021) 4, pp. 798-825

Persistent link: https://www.econbiz.de/10012637002

A note on the confidence properties of reference priors for the calibration model

Philippe, Anne; Robert, Christian P. - 1994

Persistent link: https://www.econbiz.de/10000908208

Estimation of a non-centrality parameter under Stein type like losses

Fourdrinier, Dominique; Philippe, Anne; Robert, Christian P. - 1996

Persistent link: https://www.econbiz.de/10000952885

Riemann sums for MCMC estimation and convergence monitoring

Philippe, Anne; Robert, Christian P. - 1998

Persistent link: https://www.econbiz.de/10000997342

MCMC control spreadsheets for exponentiel mixture estimation

Gruet, Marie-Anne; Philippe, Anne; Robert, Christian P. - 1998

Persistent link: https://www.econbiz.de/10000984187

Estimation of quadratic functions : noninformative priors for non-centrality parameters

Berger, James O.; Philippe, Anne; Robert, Christian P. - 1996

Persistent link: https://www.econbiz.de/10000936720

A test for stationarity versus trends and unit roots for a wide class of dependent errors

Giraitis, Liudas; Leipus, Remigijus; Philippe, Anne - In: Econometric theory 22 (2006) 6, pp. 989-1029

Persistent link: https://www.econbiz.de/10003396931

LARCH, leverage and long memory

Giraitis, Liudas; Leipus, Remigijus; Robinson, Peter M.; … - 2003

We consider the long memory and leverage properties of a model for the conditional variance of an observable stationary sequence, where the conditional variance is the square of an inhomogeneous linear combination of past values of the observable sequence, with square summable weights. This...

Persistent link: https://www.econbiz.de/10009439572