# Setting predict points

## !PVAL

!PVAL `covariate values`

is a mechanism for specifying the particular
points to be predicted for covariates modelled using
fac(.), leg(.), spl(.)
or
pol(.)
model terms. The actualpoints predicted is controlled by the
PREDICT
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
skip
in the appropriate position in ` varlist` to ignore them.
The file should only have numeric values.
` predict_points` cannot be specified for design factors.
## !GKRIGE

!GKRIGE `p `
controls the expansion of
!PVAL
lists for
fac(`X,Y`)
model terms.

For kriging prediction in 2 dimensions (`X,Y`), the user will typically
want to predict at a grid of values, not necessarily just at
data combinations.
The values at which the prediction is required can be specified
separately for `X` and `Y` using two
!PVAL
statements.
Normally, predict points will be defined for all combinations
of `X` and `Y` values.
This qualifier is required
(with optional argument
1
) to specify the lists are to be taken in parallel. The lists must be the same length if to be taken in parallel.
## !PPOINTS

!PPOINTS ` n `
influences the number of points used when
predicting splines and polynomials. The design matrix generated by
the
leg()
,
pol()
and
spl()
functions are modified to include
extra rows that are accessed by the
PREDICT
directive. The
default value of ` n ` is 21 if there is no
!PPOINTS
qualifier.
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 `].
!PPOINTS
is ignored if
!PVAL
is specified
for the variable. This process also effects the number of levels
identified by the
fac()
model term.
**Return to start**