heart                 package:rrcov                 R Documentation

_H_e_a_r_t _C_a_t_h_e_r_i_z_a_t_i_o_n _D_a_t_a

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

     This data set was analyzed by Weisberg (1980) and Chambers et al.
     (1983). A catheter is passed into a major vein or artery at the
     femoral region and moved into the heart. The proper length of the
     introduced catheter has to be guessed by the physician. The aim of
     the data set is to describe the relation between the catheter
     length and the patient's height (X1) and weight (X2).

     This data sets is used to demonstrate the effects caused by
     collinearity. The correlation between height and weight is so high
     that either variable almost completely determines the other.

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

     data(heart)

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

     A data frame with 12 observations on the following 3 variables.

     '_X_1' Patient's height in inches

     '_X_2' Patient's weights in pounds

     '_Y' Catheter Length (in centimeters)

     For convenience, the data sets 'heart.x', a matrix  with the first
     two (independent) variables of the data frame,  and 'heart.y', the
     numeric vector giving the thirth (dependent)  variable, are
     provided as well.

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

     P. J. Rousseeuw and A. M. Leroy (1987)  _Robust Regression and
     Outlier Detection._ Wiley, p.103, table 13.

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

     data(heart)
     plot(heart.x)
     covMcd(heart.x)
     summary(lm.heart <- lm(heart.y ~ heart.x))

