estMaxLik                package:dse1                R Documentation

_M_a_x_i_m_u_m _L_i_k_e_l_i_h_o_o_d _E_s_t_i_m_a_t_i_o_n

_D_e_s_c_r_i_p_t_i_o_n:

     Maximum likelihood estimation.

_U_s_a_g_e:

         estMaxLik(obj1, obj2=NULL, ...) 
         ## S3 method for class 'TSmodel':
         estMaxLik(obj1, obj2, algorithm="optim",
             algorithm.args=list(method="BFGS", upper=Inf, lower=-Inf, hessian=TRUE),
             ...)
         ## S3 method for class 'TSestModel':
         estMaxLik(obj1, obj2=TSdata(obj1), ...)
         ## S3 method for class 'TSdata':
         estMaxLik(obj1, obj2, ...) 

_A_r_g_u_m_e_n_t_s:

    obj1: an object of class TSmodel, TSdata or TSestModel

    obj2: TSdata or a TSmodel to be fitted with obj1.

algorithm: the algorithm ('optim', 'nlm' or 'nlmin') to use for
          maximization.

algorithm.args: arguments for the optimization algorithm.

     ...: arguments passed on to other methods.

_D_e_t_a_i_l_s:

     One of 'obj1' or 'obj2' should specify a 'TSmodel' and  the other
     'TSdata'. If 'obj1' is a 'TSestModel' and  'obj2' is NULL, then
     the data is extracted from 'obj1'.  The 'TSmodel' object is used
     to specify both the initial parameter  values and the model
     structure (the placement of the parameters in the various arrays
     of the TSmodel). Estimation attempts to minimimize the negative
     log likelihood (as returned by 'l' ) of the given model  structure
     by adjusting the parameter values. A 'TSmodel' can also have
     constant values in  some array elements, and these are not
     changed.

_V_a_l_u_e:

     The value returned is an object of class TSestModel with 
     additional elements 'est$converged', which is TRUE or FALSE
     indicating convergence,  'est$converceCode', which is the code
     returned by the estimation algorithm,  and 'est$results', which
     are detailed results returned by the estimation  algorithm. The
     hessian and gradient in results could potentially  be used for
     restarting in the case of non-convergence, but that has not  yet
     been implemented.

_S_e_e _A_l_s_o:

     'optim' 'nlm' 'estVARXls' 'bft' 'TSmodel' 'l'

_E_x_a_m_p_l_e_s:

       true.model <- ARMA(A=c(1, 0.5), B=1)
       est.model <-  estMaxLik(true.model,  simulate(true.model))
       summary(est.model)
       est.model
       tfplot(est.model)

