estimation_LRM {yuima} | R Documentation |
Estimation of the t-Levy Regression Model
Description
The function estimates a t-Levy Regression Model
Usage
estimation_LRM(start, model, data, upper, lower, PT = 500, n_obs1 = NULL)
Arguments
start |
Initial values to be passed to the optimizer. |
model |
A |
data |
An object of class |
upper |
A named list for specifying upper bounds of parameters. |
lower |
A named list for specifying lower bounds of parameters. |
PT |
The number of the data for the estimation of the regressor coefficients and the scale parameter. |
n_obs1 |
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 |
Details
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.
Value
Estimated parameters
Author(s)
The YUIMA Project Team
Contacts: Lorenzo Mercuri lorenzo.mercuri@unimi.it