sctest.formula          package:strucchange          R Documentation

_S_t_r_u_c_t_u_r_a_l _C_h_a_n_g_e _T_e_s_t_s

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

     Performs tests for structural change.

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

     ## S3 method for class 'formula':
     sctest(formula, type = , h = 0.15,
         alt.boundary = FALSE, functional = c("max", "range",
         "maxL2", "meanL2"), from = 0.15, to = NULL, point = 0.5,
         asymptotic = FALSE, data, ...)

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

 formula: a formula describing the model to be tested.

    type: a character string specifying the structural change test that
          ist to be performed, the default is '"Rec-CUSUM"'. Besides
          the test types described in 'efp' and 'sctest.Fstats'. The
          Chow test and the Nyblom-Hansen test can be performed by
          setting type to '"Chow"' or '"Nyblom-Hansen"', respectively.

       h: numeric from interval (0,1) specifying the bandwidth.
          Determins the size of the data window relative to sample size
          (for MOSUM and ME tests only).

alt.boundary: logical. If set to 'TRUE' alternative boundaries (instead
          of the standard linear boundaries) will be used (for CUSUM
          processes only).

functional: indicates which functional should be used to aggregate the
          empirical fluctuation processes to a test statistic.

from, to: numerics. If 'from' is smaller than 1 they are interpreted as
          percentages of data and by default 'to' is taken to be the 1
          - 'from'. F statistics will be calculated for the
          observations '(n*from):(n*to)', when 'n' is the number of
          observations in the model. If 'from' is greater than 1 it is
          interpreted to be the index and 'to' defaults to 'n - from'.
          (for F tests only)

   point: parameter of the Chow test for the potential change point.
          Interpreted analogous to the 'from' parameter. By default
          taken to be 'floor(n*0.5)' if 'n' is the  number of
          observations in the model.

asymptotic: logical. If 'TRUE' the asymptotic (chi-square) distribution
          instead of the exact (F) distribution will be used to compute
          the p value (for Chow test only).

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

     ...: further arguments passed to 'efp' or 'Fstats'.

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

     'sctest.formula' is mainly a wrapper for 'sctest.efp' and
     'sctest.Fstats' as it fits an empirical fluctuation process first
     or computes the F statistics respectively and subsequently
     performs the corresponding test. The Chow test and the
     Nyblom-Hansen test are available explicitely here.

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

     an object of class '"htest"' containing: 

statistic: the test statistic

 p.value: the corresponding p value

  method: a character string with the method used

data.name: a character string with the data name

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

     'sctest.efp', 'sctest.Fstats'

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

     ## Example 7.4 from Greene (1993), "Econometric Analysis"
     ## Chow test on Longley data
     data("longley")
     sctest(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley,
       type = "Chow", point = 7)

     ## which is equivalent to segmenting the regression via
     fac <- factor(c(rep(1, 7), rep(2, 9)))
     fm0 <- lm(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley)
     fm1 <- lm(Employed ~ fac/(Year + GNP.deflator + GNP + Armed.Forces), data = longley)
     anova(fm0, fm1)

     ## estimates from Table 7.5 in Greene (1993)
     summary(fm0)
     summary(fm1)

