BprobitEx: menus and dialogs
- Menus
- File menu
- Package menu
- Model menu
- Test menu
- Help menu
- Model Menu Dialogs
- Estimate Model dialog box
- Formulate Model dialog box (binary discrete choice)
- Formulate Model dialog box (count data)
- Model Settings dialog box (discrete choice)
- Model Settings dialog box (count data)
- Options dialog box
- Progress dialog box
- Recall dialog box
- Test Menu Dialogs
- Exclusion Restrictions dialog box
- Further output dialog box
- Graphic analysis dialog box
- Linear Restrictions dialog box
- Norm observation dialog box
- Outliers dialog box
- Predictions dialog box
- Store in database dialog
- Test dialog box
- Help
- Help
- Always on Top
-
This menu item toggles the always on top status. When switched on, OxPack
will always be above other windows, even if it does not have the focus.
When OxPack is shrunk to a small window, this could be useful to allow easy
access. When off, the OxPack will behave as a normal window.
Note that the setting is persistent between runs.
- Exit
- Exits the application.
Select BprobitEx from the Package menu
Select one of the following model classes:
- 1: Binary Discrete Choice
- 2: Count Data
The Model menu allows you to formulate and estimate models
of the selected model class,
recall a previously estimated model, check the progress made
in the modelling process.
The following commands are available:
Formulate
Model Settings
Estimate
Model Options
Progress
The Test menu is used to evaluate the model graphically,
and through diagnostic testing.
Press the F1 key for help.
Or click on the Help menu and select Help Topics to see the
help index.
Press F1 or click on the Help button in any dialog for context-specific help.
Use this dialog for to formulate a new model, or reformulate
an existing model.
- Database
-
Mark all the variables you wish to include in the new model or add to the
existing model, in this Multiple-Selection List box,
using the spacebar or the mouse.
After you have pressed Enter (or double-clicked if you are using a mouse),
the database variables are added to the model.
The variable at the top of the list will by default become the endogenous
(Y) variable.
To select a different dependent variable, see below.
- Special
-
- Constant
A constant will be added automatically in a new model but can be deleted.
- Model
-
This Multiple-Selection List box shows the current model.
The variable at the top of the list will by default become the endogenous (Y) variable.
To select a dependent variable which is listed further down:
- mark the current dependent variable and clear its status;
- mark the new variable, and press the Y:Endogenous button.
If you have marked variables in the model, you can delete them, or assign a status to them.
- Delete
-
Deletes the current model selection.
- New model
-
Deletes the whole model, so that you can start from scratch.
- Clear
-
Clears the status of all selected model variables.
Cleared variables behave as X variables.
You can also double click on a model variable to clear its status.
- Y:endogenous
-
Label the current model selection as endogenous variables.
Normally, there is one dependent variable which holds
the binary response 0 or 1 (although 1 and 2 are also allowed).
If two Y variables are marked, the data are assumed to be grouped.
- X:variable
-
Marks the selected model variables as a normal regressor. This is the
default for an unmarked variable, so an X variable or unmarked variable
are treated in the same way.
- W: weight
-
Optionally, a variable can be marked for weighted maximum likelihood
estimation.
- S: Select By
-
By default, all valid observations are used for estimation.
Select by can be used to estimate over a sub-sample.
When a model variable is marked as S variable, only observations
which have a non-zero value are included for estimation.
When predicting, the default is to use all valid observations
which were not used in estimation, but it is also possible to
only predict for observations which have a value 2 for the select by
variable.
- OK or Add
-
If there are still database variables marked, this button will be called
Add. Press it to add the variables (or press Deselect All to
change it to OK).
You will be prompted for a lag length if it is set to query.
You can also double click on a database variable to add it to the model.
Press OK to move to the Model Settings
or Estimation.
- Cancel
-
Equivalent to pressing Esc, it will abort the model formulation.
Use this dialog for to formulate a new model, or reformulate
an existing model.
- Database
-
Mark all the variables you wish to include in the new model or add to the
existing model, in this Multiple-Selection List box,
using the spacebar or the mouse.
After you have pressed Enter (or double-clicked if you are using a mouse),
the database variables are added to the model.
The variable at the top of the list will by default become the endogenous
(Y) variable.
To select a different dependent variable, see below.
- Special
-
- Constant
A constant will be added automatically in a new model but can be deleted.
- Model
-
This Multiple-Selection List box shows the current model.
The variable at the top of the list will by default become the endogenous (Y) variable.
To select a dependent variable which is listed further down:
- mark the current dependent variable and clear its status;
- mark the new variable, and press the Y:Endogenous button.
If you have marked variables in the model, you can delete them, or assign a status to them.
- Delete
-
Deletes the current model selection.
- New model
-
Deletes the whole model, so that you can start from scratch.
- Clear
-
Clears the status of all selected model variables.
Cleared variables behave as X variables.
You can also double click on a model variable to clear its status.
- Y:endogenous
-
Label the current model selection as the endogenous variable.
Only one endogenous variable, holding the counts, is allowed.
- X:variable
-
Marks the selected model variables as a normal regressor. This is the
default for an unmarked variable, so an X variable or unmarked variable
are treated in the same way.
- OK or Add
-
If there are still database variables marked, this button will be called
Add. Press it to add the variables (or press Deselect All to
change it to OK).
You will be prompted for a lag length if it is set to query.
You can also double click on a database variable to add it to the model.
Press OK to move to the Model Settings
or Estimation.
- Cancel
-
Equivalent to pressing Esc, it will abort the model formulation.
Use this dialog to recall a previously estimated model.
You will have to re-estimate it to get access to the items
on the Test Menu.
- Models
-
Move the cursor to the model you wish to recall, and press OK.
- Previous, Next
-
Use these buttons to move between the estimated models.
This dialog is for choosing a discrete choice model.
- The Model Type
-
- Logit
- Probit
Only binary probit can be estimated.
This dialog is for choosing a count data model.
- The Model Type
-
- Poisson
- Negative binomial
Select an estimation method for the formulated model.
- The Method Options
-
- Estimation sample
-
Cross-section modelling automatically drops all observations
with missing values. This can be refined by specifying a
select by variable in the model formulation stage.
- Options
-
Allows setting the estimation options.
- OK
-
Pressing OK starts the estimation, unless there still is something missing or
wrong in the dialog.
Controls maximization settings, and what is automatically printed
after estimation (in addition to the normal estimation report).
Model options referes to settings which are changed infrequently,
and are persistent between runs of OxPack.
- Maximization Settings
-
Maximum number of iterations:
Note that it is possible
that the maximum number of iterations is reached before
convergence. The maximum number of
iterations also equals the maximum number of switches in cointegration.
Write results every:
By default no iteration progress
is displayed in the results window. It is possible to write intermediate
information to the Results window for a more permanent record.
A zero (the default) will write nothing, a 1 every iteration, a
2 every other iteration, etc.
Write in compact form:
Writes one line per printed
iteration (see Write results every).
Convergence tolerance:
Change the convergence tolerance
levels (the smaller, the longer the estimation will take to converge).
See under numerical optimization for an explanation
of convergence decisions.
Default:
Resets the default maximization settings.
Use this dialog to review the progress made to date
in the model reduction, when using the general to specific
Modelling Strategy.
To offer a default sequence, OxPack decides that model A could
be nested in model B if the following conditions hold:
- model A must have a lower log-likelihood (i.e.~higher RSS),
- model A must have fewer parameters,
- model A and B must have the same sample period and database.
OxPack does not check if the same variables are involved, because
transformations could hide this. As a consequence OxPack does not
always get the correct nesting sequence, and it is the user's
responsability to ensure nesting.
There are two options on the dialog to select a nesting sequence:
- Set Specific
-
Marks more general models, finding a nesting sequence with strictly
increasing log-likelihood.
- Set General
-
Marks all specific models that have a lower log-likelihood.
The default selection is found by first setting the most recent
model as specific, and then setting the general model that was found
as the general model.
Additional dialog items are:
- Models
-
Already marked is the default nesting sequence.
However, OxPack might miss a model that
could be nested through transformed variables. You can add such models
to the nesting chain by marking them in this list box.
Marking or unmarking can be done by clicking on a model's checkbox.
Models can be moved up or down by selecting them and pressing the arrow
up or down button.
- Find Results
-
Will exit the dialog and try to locate the output
of the highlighted model in the GiveWin results window.
- Write Batch
-
Writes the batch code for the selected models.
- OK
-
Prints the progress report, consisting of:
1. number of observations, paramaters, and log-likelihood.
2. Information criteria: reported are the Schwarz Criterion (SC),
the Hannan-Quinn (HQ) Criterion, and the Akaike criterion (AIC).
3. F or Chi-squared tests of each reduction.
Allows you to select explanatory variables and test whether
they are jointly significant.
A more general form is the test for linear restrictions.
- Selection
-
Mark all the variables you wish to include in the test in this
Multiple-Selection List box.
OxPack tests whether the selected variables can be deleted from the model.
Tests for linear restrictions
are specified in the form of a matrix R, and a vector r.
These are entered as one matrix [R : r] in the dialog.
(This is a more general than testing for
exclusion restrictions.)
For example, if the model is CONS on Constant, CONS_1, INC, INC_1,
and we wish to test that the coefficients on INC and INC_1 add up to
one, and that on CONS_1 equals zero. Then the R:r matrix can be written as
<![CDATA[
0 1 0 0 0
0 0 1 1 1
]]>
The first four columns are the columns of R, specifying two
restrictions. The last column is r, which specifies what the
restrictions should add up to.
The dimensions of the matrix must be specified in the rows and
columns fields. It is your responsibility to specify the right values,
OxPack will not try to work it out (because elements of a row may be
spread over several lines).
- Rows
-
The number of rows in the matrix.
- Columns
-
The number of columns in the matrix.
- Matrix
-
This window is a basic text editor in which you can edit a
matrix file. Here you can enter the R:r matrix
as in the above example.
- Set to zero
-
This could be useful to create an initial matrix. Select variables
in the model box (this is a this multiple-selection list box).
and press this button to specify the R:r matrix which corresponds
to the restriction that each selected variable has coefficient zero
(so one row for each selected variable)
- Load
-
Enables you to load an existing matrix file into
the editor.
Any existing matrix in the editor will be lost.
- Save
-
Enables you to save the contents of the editor in an matrix file,
so that it can be used again.
A multiple selection list box allows for marking as many items as desired.
With the keyboard it is only possible to mark a single variable (by using the arrow up and down keys), or range of variables (hold the Shift key down while using the arrow up or down keys).
With the mouse there is more flexibility:
- single click to select one variable;
- hold the left mouse button down to select a range of variables;
- hold the Ctrl key down and click to select additional variables;
- hold the Shift key down and click to extend the selection range.
OxPack has two modes of operation: general-to-specific and unordered.
- General-to-specific
-
1. Begin with the model formulation;
2. Check its data coherence and cointegration;
3. Transform to a set of variables with low intercorrelations but interpretable parameters;
4. Delete unwanted regressors to obtain a parsimonious model;
5. Check the validity of the model by thorough testing and graphical inspection.
OxPack monitors the progress of the sequential reduction from the
general to the specific and will provide the associated F-tests or likelihood-ratio
tests, and information criteria.
- Unordered Search
-
Nothing commends unordered searches:
1. No control is offered over the significance level of testing;
2. A `later' reject outcome invalidates all earlier ones;
3. Until a model adequately characterizes the data, standard tests are invalid
This file last changed .