vis.gam                 package:mgcv                 R Documentation

_V_i_s_u_a_l_i_z_a_t_i_o_n _o_f _G_A_M _o_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Produces perspective plot views of 'gam' model predictions, fixing
     all but the values in 'view' to the  values supplied in 'cond'.
     Replaces 'persp.gam'.

_U_s_a_g_e:

     vis.gam(x,view=NULL,cond=list(),n.grid=30,too.far=0,col=NA,
             color="topo",se=-1,type="link",zlim=NULL,...)

_A_r_g_u_m_e_n_t_s:

       x: a 'gam' object, produced by 'gam()'

    view: an array containing the names of the two predictor variables
          to be displayed on the  x and y dimensions of the plot. If
          omitted the first two suitable variables will be used

    cond: a named list of the values to use for the other predictor
          variables (not in 'view'). Variables omitted from  this list
          will have their values set to their mean for continuous
          variables, or first level for factors.

  n.grid: The number of grid nodes in each direction used for
          calculating the  plotted surface.

 too.far: plot grid nodes that are too far from the points defined by
          the variables given in 'view'  can be excluded from the plot.
          'too.far' determines what is too far. The grid is scaled into
          the unit  square along with the 'view' variables and then
          grid nodes more than 'too.far' from the predictor variables 
          are excluded.

     col: The colours for the facets of the plot. If this is 'NA' then
          if 'se'>0 the facets are transparent,  otherwise the colour
          scheme specified in 'color' is used. If 'col' is not 'NA'
          then it is used as the facet  colour.

   color: the colour scheme to use for plots when 'se'<=0. One of
          '"topo"', '"heat"', '"cm"' or  '"terrain"'.

      se: if less than or equal to zero then only the predicted surface
          is plotted, but if greater than zero, then 3  surfaces are
          plotted, one at the predicted values minus 'se' standard
          errors, one at the predicted values and one at the predicted
          values plus 'se' standard errors.

    type: '"link"' to plot on linear predictor scale and '"response"'
          to plot on the response scale.

    zlim: a two item array giving the lower and upper limits for the
          z-axis scale. 'NULL' to choose automatically.

     ...: other options to pass on to 'persp'. In particular
          'ticktype="detailed"' will add proper axes  labelling to the
          plots.

_D_e_t_a_i_l_s:

     The x and y limits are determined by the ranges of the variables
     supplied in 'view'. If 'se'<=0 then  a single (height colour
     coded, by default) surface is produced, otherwise three (by
     default see-through) meshes are produced at  mean and +/- 'se'
     standard errors. Parts of the x-y plane too far from data can be
     excluded by setting 'too.far'

_V_a_l_u_e:

     Simply produces a plot.

_A_u_t_h_o_r(_s):

     Simon Wood simon@stats.gla.ac.uk, based on an original idea and
     design by Mike Lonergan.

_S_e_e _A_l_s_o:

     'persp' and 'gam'.

_E_x_a_m_p_l_e_s:

     library(mgcv)
     set.seed(0)
     n<-200;sig2<-4
     x0 <- runif(n, 0, 1);x1 <- runif(n, 0, 1)
     x2 <- runif(n, 0, 1)
     y<-x0^2+x1*x2 +runif(n,-0.3,0.3)
     g<-gam(y~s(x0,x1,x2))
     old.par<-par(mfrow=c(2,2))
     # display the prediction surface in x0, x1 ....
     vis.gam(g,ticktype="detailed",color="heat",theta=-35)  
     vis.gam(g,se=2,theta=-35) # with twice standard error surfaces
     vis.gam(g, view=c("x1","x2"),cond=list(x0=0.75)) # different view 
     vis.gam(g, view=c("x1","x2"),cond=list(x0=0.75),theta=210,phi=40,too.far=0.07)
     # ..... areas where there is no data are not plotted
     par(old.par)

     # Examples with factor and "by" variables

     fac<-rep(1:4,20)
     x<-runif(80)
     y<-fac+2*x^2+rnorm(80)*0.1
     fac<-factor(fac)
     b<-gam(y~fac+s(x))

     vis.gam(b,theta=-35,color="heat") # factor example

     z<-rnorm(80)*0.4   
     y<-as.numeric(fac)+3*x^2*z+rnorm(80)*0.1
     b<-gam(y~fac+s(x,by=z))

     vis.gam(b,theta=-35,color="heat",cond=list(z=1)) # by variable example

     vis.gam(b,view=c("z","x"),theta= 35) # plot against by variable

