cement                package:monomvn                R Documentation

_H_a_l_d'_s _C_e_m_e_n_t _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     Heat evolved in setting of cement, as a function of its chemical
     composition.

_U_s_a_g_e:

     data(cement)
     data(cement.miss)

_F_o_r_m_a_t:

     A 'data.frame' with 13 observations on the following 5 variables.

     _x_1  percentage weight in clinkers of 3CaO.Al2O3

     _x_2  percentage weight in clinkers of 3CaO.SiO2

     _x_3  percentage weight in clinkers of 4CaO.Al2O3.Fe2O3

     _x_4  percentage weight in clinkers of 2CaO.SiO2

     _y  heat evolved (calories/gram)

_D_e_t_a_i_l_s:

     'cement.miss' is taken from an example in Little & Rubin's book on
     _Statistical Analysis with Missing Data_ (2002), pp.~154, for
     demonstrating estimation of multivariate means and variances when
     the missing data pattern is monotone.  These are indicated by 'NA'
     in 'cement.miss'.  See the examples section of 'monomvn' for a
     re-working of the example from the textbook

_S_o_u_r_c_e:

     Woods, H., Steinour, H. H. and Starke, H. R. (1932)  Effect of
     composition of Portland cement on heat evolved during hardening.
     _Industrial Engineering and Chemistry_, *24*, 1207-1214.

_R_e_f_e_r_e_n_c_e_s:

     Davison, A. C. (2003)  _Statistical Models_.  Cambridge University
     Press. Page 355.

     Draper, N.R. and Smith, H. (1998) _Applied Regression Analysis_.
     Wiley. Page 630.

     Roderick J.A. Little and Donald B. Rubin (2002). _Statistical
     Analysis with Missing Data_, Second Edition. Wilely.  Page 154.

     <URL: http://www.statslab.cam.ac.uk/~bobby/monomvn.html>

_S_e_e _A_l_s_o:

     'monomvn' -  Several other R packages also include this data set

_E_x_a_m_p_l_e_s:

     data(cement)
     lm(y~x1+x2+x3+x4,data=cement)

