scaleParameterPlot            package:plw            R Documentation

_S_c_a_l_e _p_a_r_a_m_e_t_e_r _p_l_o_t_t_e_d _a_g_a_i_n_s_t _m_e_a_n _i_n_t_e_n_s_i_t_y

_D_e_s_c_r_i_p_t_i_o_n:

     Will produce a scatter plot of variance estimators (logged) for
     each probe (probe set) against the corresponding mean intensity
     together with the fitted scale-parameter curve and points showing
     the knots of the used spline.

_U_s_a_g_e:

     scaleParameterPlot(model,main="Scale parameter curve",
                col=1,pch='.',lty=1,curveCol=2,knotsPch=19,knotsCol=3)

_A_r_g_u_m_e_n_t_s:

   model: On object obtained from the function plw or lmw.

    main: Main title of plot.

     col: Color for individual points (mean,logs2).

     pch: Plot symbol for individual points (mean,logs2).

     lty: Line type for fitted scale parameter curve.

curveCol: Line color for fitted scale parameter curve.

knotsPch: Plot symbol for spline knots.

knotsCol: Plot color for spline knots.

_A_u_t_h_o_r(_s):

     Magnus Astrand

_S_e_e _A_l_s_o:

     plw, lmw

_E_x_a_m_p_l_e_s:

     # ------------------------------------------
     # Example using the result of the analysis of
     # the 6 arrays in the AffySpikeU95Subset data set

     # Loading the data
     data(AffySpikeU95Subset)

     # Defining design and contrast matrix
     group<-factor(rep(1:2,each=3))
     design<-model.matrix(~group-1)
     contrast<-matrix(c(1,-1),1,2)

     # Analyzing using plw
     model1<-plw(AffySpikeU95Subset,design=design,contrast=contrast,
                 epsilon=0.01)

     ## Look at fitted curve for scale parameter
     scaleParameterPlot(model1)

