sheet—469

tab1.setwidth(2:10) 20

sets the widths for columns 2 through 10 to 20 width units.

Cross-references

See setindent (p. 462) and setjust (p. 463) for details on setting spreadsheet and table indentation and justification. For details on setting the row heights in a table, see setheight (p. 461).

For additional discussion of tables see Chapter 4, “Working with Tables”, on page 47. See also Chapter 14, “Graphs, Tables, and Text Objects”, on page 413 of the User’s Guide for a discussion and examples of table formatting in EViews.

Spreadsheet view of object.

The sheet view displays the spreadsheet view of the named object. For table objects, sheet simply displays the table.

Syntax

The sheet view of pool objects displays the spreadsheet view of the series in the pool. Follow the word sheet by a list of series to display; you may use the cross section identifier “?” in the series name.

Options

Examples

tab1.sheet

displays the spreadsheet view of TAB1.

pool1.sheet x? y? z?

displays the pool spreadsheet view of the series X?, Y?, and Z?.

470—Appendix B. Command Reference

Cross-references

See Chapter 5, “Basic Data Handling”, on page 85 of the User’s Guide for a discussion of the spreadsheet view of series and groups, and Chapter 27, “Pooled Time Series, CrossSection Data”, on page 823 of the User’s Guide for a discussion of pools.

Display objects.

The show command displays series or other objects on your screen. A scalar object is displayed in the status line at the bottom of the EViews window.

Syntax

Command: show object_name.view_command

Command: show object1 [object2 object3 ...]

The command show should be followed by the name of an object, or an object name with an attached view.

For series and graph objects, show can operate on a list of names. The list of names must be of the same type. show creates and displays an untitled group or multiple graph object.

Examples

genr x=nrnd

show x.hist

close x

generates a series X of random draws from a standard normal distribution, displays the histogram view of X, and closes the series window.

show wage log(wage)

opens an untitled group window with the spreadsheet view of the two series.

freeze(gra1) wage.hist

genr lwage=log(wage)

freeze(gra2) lwage.hist

show gra1 gra2

opens an untitled graph object with two histograms.

472—Appendix B. Command Reference

Exponential smoothing.

Forecasts a series using one of a number of exponential smoothing techniques. By default, smooth estimates the damping parameters of the smoothing model to minimize the sum of squared forecast errors, but you may specify your own values for the damping parameters.

smooth automatically calculates in-sample forecast errors and puts them into the series RESID.

Syntax

Command: smooth(method) series_name smooth_name [freq]

You should follow the smooth keyword with the name of the series and a name for the smoothed series. You must also specify the smoothing method in parentheses. The optional freq may be used to override the default for the number of periods in the seasonal cycle. By default, this value is set to the workfile frequency (e.g. — 4 for quarterly data). For undated data, the default is 5.

Options

Smoothing method options

smooth—473

Other Options:

If you wish to set only some of the damping parameters and let EViews estimate the other parameters, enter the letter “e” where you wish the parameter to be estimated.

If the number of seasons is different from the frequency of the workfile (an unusual case that arises primarily if you are using an undated workfile for data that are not monthly or quarterly), you should enter the number of seasons after the smoothed series name. This optional input will have no effect on forecasts without seasonal components.

Examples

smooth(s) sales sales_f

smooths the SALES series by a single exponential smoothing method and saves the smoothed series as SALES_F. EViews estimates the damping (smoothing) parameter and displays it with other forecast statistics in the SALES series window.

smooth(n,e,.3) tb3 tb3_hw

smooths the TB3 series by a Holt-Winters no seasonal method and saves the smoothed series as TB3_HW. The mean damping parameter is estimated while the trend damping parameter is set to 0.3.

smpl @first @last-10

smooth(m,.1,.1,.1) order order_hw

smpl @all

graph gra1.line order order_hw

show gra1

smooths the ORDER series by a Holt-Winters multiplicative seasonal method leaving the last 10 observations. The damping parameters are all set to 0.1. The last three lines plot and display the actual and smoothed series over the full sample.

Cross-references

See “Exponential Smoothing” on page 348 of the User’s Guide for a discussion of exponential smoothing methods.