gqtest                package:lmtest                R Documentation

_G_o_l_d_f_e_l_d-_Q_u_a_n_d_t-_T_e_s_t

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

     `gqtest' performs the Goldfeld-Quandt-Test against
     heteroskadasticity. Given a known time `T', the Goldfeld-Quandt
     tests the null-hypothesis: variances at time 1..T and T..n are
     equal.

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

     gqtest(formula, T, data=list())

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

 formula: a symbolic describtion for the model to be tested

       T: split the model at time T

    data: an optional data frame containing the variables in the model.
          By default the variables are taken from the environment which
          'gqtest' is called from

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

     The test statistic under H0 follows a F distribution with df1 and
     df2 degree of freedom.

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

     A list with class `"htest"' containing the following components: 

statistic: the value of the test statistic.

 p.value: the p-value of the test.

  method: a character string indicating what type of test was
          performed.

data.name: a character string giving the name(s) of the data.

_A_u_t_h_o_r(_s):

     Torsten Hothorn <Torsten.Hothorn@rzmail.uni-erlangen.de>

_R_e_f_e_r_e_n_c_e_s:

     Kraemer, W., Sonnberger, H. (1986): The linear regression model
     under test

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

     `lm'

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

     x <- c(1:30);
     err <- c(rnorm(10,0,1), rnorm(20,0,10));
     y <- x + err;
     formular <- y ~ x;
     gq <- gqtest(formular, 10);
     qf(0.95, gq$parameter[1], gq$parameter[2]);

