The function estimates a t-Levy Regression Model
estimation_LRM(start, model, data, upper, lower, PT = 500, n_obs1 = NULL)Estimated parameters
Initial values to be passed to the optimizer.
A yuima.LevyRM-class that contains the mathematical representation of the t-Levy Regression Model. Its slot @data can contain either real or simulated data.
An object of class yuima.data-class contains the observations available at uniformly spaced time. If data=NULL, the default, the function uses the data in the object model.
A named list for specifying upper bounds of parameters.
A named list for specifying lower bounds of parameters.
The number of the data for the estimation of the regressor coefficients and the scale parameter.
The number of data used in the estimation of the degree of freedom. As default the number of the whole data is used in this part
The YUIMA Project Team
Contacts: Lorenzo Mercuri lorenzo.mercuri@unimi.it
A two-step estimation procedure. Regressor coefficients and scale parameters are obtained by maximizing the quasi-likelihood function based on the Cauchy density. The degree of freedom is estimated used the unitary increment of the t-noise.