sdflm2               package:SQLiteDF               R Documentation

_L_i_n_e_a_r _M_o_d_e_l_s _o_n _S_Q_L_i_t_e _D_a_t_a _F_r_a_m_e_s

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

     biglm specialized for SQLite Data Frames

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

     sdflm2(x, y, intercept = TRUE)

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

       x: a SQLite data frame containing the design matrix which may
          not include the intercept 

       y: a SQLite vector containing the observed response 

intercept: if TRUE, adds an intercept term when doing computation 

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

     Algorithm is identical with 'biglm'. The only difference is that
     the rows of 'x' and the values of 'y' are directly fed to the
     algorithm.

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

     Returns a subclass of 'biglm'. 'biglm' methods can be used with
     the output, e.g. compute coefficients, vcov, etc.

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

     Miguel A. R. Manese

_R_e_f_e_r_e_n_c_e_s:

     Algorithm AS274  Applied Statistics (1992) Vol.41, No. 2

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

     'biglm '

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

         library(biglm)
         iris.sdf <- sqlite.data.frame(iris)
         x <- iris.sdf[,1:3]
         y <- iris.sdf[,4]
         iris.biglm <- sdflm2(x, y)
         summary(iris.biglm)

