The two command-line arguments may be:
REGION-PROJECTION Command Arguments
| <sherpa_modelname>.{<paramname> | <#>} |
A specified model component parameter (e.g., GAUSS.pos). |
| <modelname>.{<paramname> | <#>} |
A specified model component parameter (e.g., g.pos). |
The user may configure REGION-PROJECTION via
the Sherpa state object structure regproj.
The current values of the fields of this structure may be
displayed using the command print(sherpa.regproj),
or using the more verbose Sherpa/S-Lang module
function list_regproj().
The structure fields are:
regproj Structure Fields
| fast |
If 1, use a fast optimization algorithm
(LEVENBERG-MARQUARDT
or
SIMPLEX)
regardless of the current
METHOD.
If 0, use the current
METHOD. |
| expfac |
A multiplicative factor that expands the grid limits estimated by the
COVARIANCE
algorithm, if
the grid limits are determined automatically (see arange,
and below).
|
| arange |
If 1, the grid limits are to be determined automatically. If 0, the
grid limits are specified (see min and max).
|
| min |
An array of length two giving the grid minima for each plot axis.
These are always linear quantities, regardless of the setting of
log (see below).
The array is ignored if arange = 1.
|
| max |
An array of length two giving the grid maxima for each plot axis.
These are always linear quantities, regardless of the setting of
log (see below).
The array is ignored if arange = 1.
|
| log |
An array of length two specifying whether to use linear (0) or
logarithmic (1) spacing of grid points along each plot axis.
|
| nloop |
An array of length two specifying the number of grid points along
each plot axis.
|
| sigma |
An array of arbitrary length specifying the number of
sigma for each
contour. The length of the array specifies the number of contours.
|
Field values may be set using directly. If the field does not contain an
array, e.g.,
sherpa> sherpa.regproj.arange = 0
and if it does contain an array, e.g.,
sherpa> sherpa.regproj.nloop = [25,20]
NOTE: strict checking of value inputs is not done,
i.e., the user can errantly change arrays to scalars,
etc. To restore the default settings of the structure
at any time, use the Sherpa/S-Lang module function
restore_regproj().
The confidence regions are determined by varying each selected
parameter's value on the determined (arange = 1) or
specified (arange = 0)
grid, computing the best-fit statistic at each grid point, and
interpolating on the grid. REGION-PROJECTION differs from
REGION-UNCERTAINTY in
that all other thawed parameters are allowed to float to new best-fit
values, instead of being fixed to their best-fit values. This makes
REGION-PROJECTION contours more accurate, but causes
their computation to proceed more slowly. For a fuller theoretical
description of error estimation, see PROJECTION, UNCERTAINTY, and COVARIANCE.
If arange = 1, then the grid limits for
the plot are determined automatically. For increased speed, the grid
limits are determined using the error estimates from
COVARIANCE. The covariance errors
are computed assuming a change in fit statistic from the best-fit
value of delta_S, which is a function of
the largest value of sigma
(e.g., delta_S = 11.8
if the statistic is chi-square and
3 is the largest element of the array sigma.
The covariance errors are then multiplied by
expfac and are subtracted
from and added to the best-fit parameter values to determine the
lower and upper grid limits.
Note that the output of COVARIANCE may be adversely
affected if the problem is not well-posed (since a matrix inversion is
involved in the error calculation), or if the fit did not
reach its local minimum. If the plot does not appear correct, consider
running COVARIANCE to check the errors, and/or setting
the plot limits manually.
For increased speed, the best fit at each grid point is calculated
using the LEVENBERG-MARQUARDT
optimization method if fast = 1 and
a chi-square statistic is used to fit;
the user's chosen optimization method is
then reset after the plot is shown.
(If fast = 1 and a non-chi-square
statistic is used during fitting, then the
SIMPLEX
method is used instead.)
The grid-point values and best-fit statistics at each grid point may
be retrieved using the Sherpa/S-Lang module function
get_regproj. See the examples below.
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