# Other Very Rarely used qualifiers

## Introduction

Qualifiers are described in 4 sections based on frequency of use.
general syntax
The
major qualifiers
are
!CONTINUE, !CONTRAST, !FCON, !MAXIT, !SUBSET, !SUM
and XYplots (
!X !Y !G !JOIN
)
Minor qualifiers
Special qualifiers
The qualifiers described here are other rarely required qualifiers.
They include

Additional output:
!CINV, !REPORT, !SCORE, !VRB

Adjusting detection of singularities in the
mixed model equations:
!TOLERANCE,

Setting covariate grouping levels:
!FACPOINTS, !POLPOINTS,

## !CINV

ASReml does not compute the whole C-inverse matrix but only
sufficient to calculate the REML solution. The user may
request that the part that is calculated be written to a .cii
file.
!CINV ` n `
prints the portion of the inverse of the coefficient matrix (C)
pertaining to the `n`th term in the linear model,
or if `n` is 1 or omitted, pertaining to all the random (sparse) terms.
Because the model has not been defined when ASReml reads this line,
it is up to the user to count the terms in the model to identify the
portion of the inverse of the coefficient matrix to be printed.
The option is ignored if the portion is not wholly in the
SPARSE
stored
equations. The portion of the inverse is printed to a file with extension
.cii.
The sparse form
of the matrix only is printed in the form

`i
j
Cij`

that is,
elements of the C inverse that were not needed in the estimation process
are not included in the file.
## Setting covariate grouping levels:

The fac()
and pol() model terms need to classify a covariate
into discrete classes. This is usually done on the basis of
unique covariate values. However, ASReml will actually consider
close points as being the same. This is controlled by
!FACPOINTS and !POLPOINTS
qualifiers respectively.
## Imputation

!IMPUTE [` n`]
is a special developmental option proposed for fitting large models
by splitting the model, fitting the reduced models alternately after
adjusting for effects in the other submodel, with added error.
The submodels are defined using the
!SM ` m`
qualifier in the model line.
More
!SM [` m`]
can be used as a data line qualifier in conjunction
with
!SM [` m`]
as a model qualifier to fit the selected submodel
without added error.
## Transformed data scratch file.

!NOSCRATCH
forces ASReml to
hold the data in memory. ASReml will usually hold the data on a scratch file rather than in memory.
In large jobs, the system area where scratch files are held may not
be large enough. A
Unix system may put this file in the
/tmp
directory
which may not have enough space to hold it.
If ASReml crashes, it may leave large temporary files in /tmp
which should be periodically checked and cleaned out.
## Standard output report

!REPORT
forces ASReml to attempt
to produce the standard output report when there is a failure of the iteration algorithm.
Usually no report is produced unless the algorithm has at least produced estimates for the
fixed and random effects in the model. Note that residuals are not included in the output forced by this qualifier.
This option is primarily intended to help debugging a job that is not converging properly.
## Exporting the AI matrix and Score

!SCORE
requests ASReml write the SCORE vector and the
Average Information matrix to files
` basename`.SCO
and
` basename`.AIM.
The values written are from the last iteration.
## Singularity detection tolerance

!TOLERANCE [`s`_{1}/var> [ `s`_{2}/var>]]
modifies the ability of ASReml to detect singularities
in the mixed model equations.
This is intended for use on the rare occasions when ASReml detects
singularities after the
first iteration (they are not expected then), or it finds the
variances of fixed effects are suspiciously large.
ASReml will give a warning when the
!TOLERANCE
qualifier may be needed.
Normally (when
!TOLERANCE
is not specified),
a singularity is declared if the adjusted sum of
squares of a covariable is less than `eta` or less than the
uncorrected sum of squares times
`eta`, where `eta` is `10`^{-8}
in the first iteration and `10`^{-10} thereafter.
The qualifier scales `eta` by `10`^{si/sup>} for the the first or subsequent iterations
respectively,
so that it is more likely an equation will be declared singular.
Once a singularity is detected, the corresponding equation is dropped
(forced to be zero) in subsequent iterations.
If neither argument is supplied, 2 is assumed. If the second argument
is omitted, it is given the value of the first.
If the problem of later singularities arises because of the low coefficient of variation
of a covariable, it would be better to centre and rescale the covariable.
If the degrees of freedom are correct in the first iteration,
the problem will be with the variance parameters and a different
variance model (or variance constraints) is required.
## The .vrb file

!VRB
requests writing of the
.vrb
file. Previously, the default was to write the file but it is
rarely needed. It contains the values of the residual variance,
the fixed effects and the variance of the fixed effects in
triangle rowwise order.
**Return to start**