Setting predict points
!PVAL covariate values
is a mechanism for specifying the particular
points to be predicted for covariates modelled using
fac(.), leg(.), spl(.)
model terms. The actualpoints predicted is controlled by the
directive. The points are specified here so that they
can be included in the appropriate design matrices.
covariate is the name of a data field.
values is the list of values
at which prediction is required.
!PVAL filename varlist
is used to read predict_points for several
variables from a file filename.
varlist is the
names of the variables having values defined.
If the file contains unwanted fields, put the
pseudo variate label
in the appropriate position in varlist to ignore them.
The file should only have numeric values.
predict_points cannot be specified for design factors.
controls the expansion of
For kriging prediction in 2 dimensions (X,Y), the user will typically
want to predict at a grid of values, not necessarily just at
The values at which the prediction is required can be specified
separately for X and Y using two
Normally, predict points will be defined for all combinations
of X and Y values.
This qualifier is required
(with optional argument
) to specify the lists are to be taken in parallel. The lists must be the same length if to be taken in parallel.
influences the number of points used when
predicting splines and polynomials. The design matrix generated by
functions are modified to include
extra rows that are accessed by the
default value of n is 21 if there is no
The range of the data is divided by n-1 to give a
step size i . For each point p in the list
of unique covariate values, a predict point
is inserted at p + i if there is no data value in the
interval [ p , p +1.1 i ].
is ignored if
for the variable. This process also effects the number of levels
identified by the
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