norMix                package:nor1mix                R Documentation

_M_i_x_t_u_r_e_s _o_f _U_n_i_v_a_r_i_a_t_e _N_o_r_m_a_l _D_i_s_t_r_i_b_u_t_i_o_n_s

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

     Objects of class 'norMix' represent finite mixtures of
     (univariate) normal (aka Gaussian) distributions.  Methods for
     construction, printing, plotting, and basic computations are
     provided.

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

     norMix(mu, sig2 = rep(1,m), w = NULL, name = NULL, long.name = FALSE)

     is.norMix(obj)
     m.norMix(obj)
     mean.norMix(x, ...)
     var.norMix(x, ...)
     ## S3 method for class 'norMix':
     print(x, ...)

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

      mu: numeric vector of length K, say, specifying the means mu of
          the K normal components.

    sig2: numeric vector of length K, specifying the variances sigma^2
          of the K normal components.

       w: numeric vector of length K, specifying the mixture
          proportions p[j] of the normal components, j = 1,...,K.
          Defaults to equal proportions

    name: optional name tag of the result (used for printing).

long.name: ~~Describe 'long.name' here~~ 

  obj,x : an object of class 'norMix'.

     ...: further arguments passed to methods.

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

     The (one dimensional) normal mixtures, R objects of class
     '"norMix"', are constructed by 'norMix' and tested for by
     'is.norMix'.  'm.norMix()' returns the number of mixture
     components, .... For further methods see below.

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

     'norMix' returns objects of class '"norMix"' which are currently
     implemented as 3-column matrix with column names 'mu', 'sig2', and
     'w', and further attributes. The user should rarely need to access
     the underlying structure directly.

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

     Martin Maechler

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

     'dnorMix' for the density, 'rnorMix' for random numbers and
     'print.norMix', the plot method.

     'MarronWand' has the Marron-Wand densities as normal mixtures.

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

     ex <- norMix(mu = c(1,2,5))# s^2 = 1, equal proportions
     ex
     plot(ex)# looks like a mixture of only 2

     plot(ex, log = "y")# maybe "revealing"

