missvals               package:mvnmle               R Documentation

_A _m_u_l_t_i_v_a_r_i_a_t_e _d_a_t_a _s_e_t _w_i_t_h _m_i_s_s_i_n_g _v_a_l_u_e_s

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

     The `missvals' data frame has 13 rows and 5 columns. These are
     data from Draper and Smith (1968), and are included to demonstrate
     ML estimation of mean and variance-covariance parameters of
     multivaraite normal data when some observations are missing.

_F_o_r_m_a_t:

     This data frame contains the following columns:

     _x_1-_x_5 numeric vectors

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

     These data constitute Table 6.4 in Little and Rubin (1987).  They
     are analyzed both in Rubin (1976) and Little and Rubin (1987).

_S_o_u_r_c_e:

     Draper, N. R., and Smith, H.  (1968).  Applied Regression
     Analysis.  New York: Wiley.

     Little, R. J. A., and Rubin, D. B. (1987) Statistical Analysis
     with Missing Data.  New York: Wiley.

     Rubin, D. B.  (1976)  Comparing regressions when some predictor
     variables are missing.  Psychometrika 43, 3-10.

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

     library(mvnmle)
     data(missvals)

     mlest(missvals, iterlim=400)

