boxplotby—225
ci=arg |
95% confidence interval for median: “none” (do not |
(default= |
display), “shade” (display interval as shaded area), |
“shade”) |
“notch” (display interval using notched boxes). |
Options to control calculation of boxplots
b |
Balance sample. |
|
|
q=arg |
Compute quantiles using the specified definition: “b” |
(default=“r”) |
(Blom), “r” (Rankit-Cleveland), “o” (simple fraction), |
|
“t” (Tukey), “v” (van der Waerden). |
Other options
p Print the view.
Examples
grp1.boxplot
displays default boxplots for all of the series in the group GRP1.
grp2.boxplot(b, nowhisk)
displays boxplots for the series in GRP2 after balancing the sample. The boxplots will not have whiskers drawn.
Cross-references
See “Boxplots” on page 407 of the User’s Guide for additional discussion.
See also boxplotby (p. 225) and stats (p. 487). For customization of a boxplot graph object, see setelem (p. 449) and setbpelem (p. 445).
boxplotby |
Series View |
|
|
Display the boxplots of a series classified into categories.
Create a boxplot graph view containing boxplots of the elements of a series classified into categories by one or more series.
Syntax
Series View: |
series_name.boxplotby(options) classifier_names |
Follow the series name with a period, the keyword, and a name (or a list of names) for the series or groups by which to classify. The default settings are to display fixed width box-
226—Appendix B. Command Reference
plots for each category, with all basic elements drawn (mean, med, staples, whiskers, near outliers, far outliers), and with shading representing the approximate confidence intervals for the median.
Options
Options to control display
nomean |
Do not display means. |
|
|
nomed |
Do not display medians. |
|
|
nostaple |
Do not display staples. |
|
|
nowhisk |
Do not display whiskers. |
|
|
nonearout |
Do not display near outliers. |
|
|
nofarout |
Do not display far outliers. |
|
|
nolabel |
Do not display axis labels. |
|
|
width=arg |
Boxplot width: “fixed” (fixed width boxplots), “n” |
(default= |
(width proportional to number of observations), |
“fixed”) |
“rootn” (width proportional to square root of number of |
|
observations). |
|
|
ci=arg |
95% confidence interval for median: “none” (do not |
(default= |
display), “shade” (display interval as shaded area), |
“shade”) |
“notch” (display interval using notched boxes). |
|
|
Options to control calculation of boxplots
dropna (default), |
[Drop/Keep] NA as a category. |
keepna |
|
|
|
total |
Create category for entire series. |
|
|
q=arg |
Compute quantiles using the specified definition: “b” |
(default=“r”) |
(Blom), “r” (Rankit-Cleveland), “o” (simple fraction), |
|
“t” (Tukey), “v” (van der Waerden). |
|
|
Options to control binning
v=integer |
Bin categories if classification series take on more than |
(default=100) |
the specified number of distinct values. |
|
|
nov |
Do not bin based on the number of values of the classi- |
|
fication series. |
bpf—227
a=number |
Bin categories if average cell count is less than the spec- |
(default=2) |
ified number. |
|
|
noa |
Do not bin based on the average cell count. |
|
|
b=integer |
Set maximum number of binned categories. |
(default=5) |
|
|
|
Other options
p |
Print the view. |
|
|
Examples
wage.boxplotby sex race
displays boxplots for the series WAGE categorized by the values of SEX and RACE.
income.boxplotby(total, keepna, width=n) sex race
displays boxplots for INCOME classified by SEX and RACE, with missing values in the classifier series treated as categories, and an additional boxplot drawn for the entire sample of observations. The boxes will be drawn with variable widths proportional to the number of observations in each category.
Cross-references
See “Boxplots” on page 407 of the User’s Guide.
See also boxplot (p. 224), and statby (p. 482). For customization of a boxplot graph object, see setelem (p. 449) and setbpelem (p. 445).
bpf |
Series Proc |
|
|
Compute and display the band-pass filter of a series.
Computes, and displays a graphical view of the Baxter-King fixed length symmetric, Chris- tiano-Fitzgerald fixed length symmetric, or the Christiano-Fitzgerald full sample asymmetric band-pass filter of the series.
The view will show the original series, the cyclical component, and non-cyclical component in a single graph. For non time-varying filters, a second graph will show the frequency responses.
Syntax
Series Proc: |
series_name.bpf(options) [cyc_name] |
228—Appendix B. Command Reference
Follow the bpf keyword with any desired options, and the optional name to be given to the cyclical component. If you do not provide cyc_name, the filtered series will be named BPFILTER## where ## is a number chosen to ensure that the name is unique.
Options
type=arg
(default=“bk”)
Specify the type of band-pass filter: “bk” is the BaxterKing fixed length symmetric filter, “cffix” is the Chris- tiano-Fitzgerald fixed length symmetric filter, “cfasym” is the Christiano-Fitzgerald full sample asymmetric filter.
low=number, |
Low (PL ) and high (PH ) values for the cycle range to |
high=number |
be passed through (specified in periods of the workfile |
|
frequency). |
|
Defaults to the workfile equivalent corresponding to a |
|
range of 1.5–8 years for semi-annual to daily workfiles; |
|
otherwise sets “low=2”, “high=8”. |
|
The arguments must satisfy 2 ≤ PL < PH . The corre- |
|
sponding frequency range to be passed through will be |
|
(2π ⁄ PH, 2π ⁄ PL) . |
|
|
lag=integer |
Fixed lag length (positive integer). Sets the fixed lead/ |
|
lag length for fixed length filters (“type=bk” or |
|
“type=cffix”). Must be less than half the sample size. |
|
Defaults to the workfile equivalent of 3 years for semi- |
|
annual to daily workfiles; otherwise sets “lag=3”. |
|
|
iorder=[0,1] |
Specifies the integration order of the series. The default |
(default=0) |
value, “0” implies that the series is assumed to be |
|
(covariance) stationary; “1” implies that the series con- |
|
tains a unit root. |
|
The integration order is only used in the computation of |
|
Christiano-Fitzgerald filter weights (“type=cffix” or |
|
“type=cfasym”). When “iorder=1”, the filter weights |
|
are constrained to sum to zero. |
bpf—229
detrend=arg |
Detrending method for Christiano-Fitzgerald filters |
(default=“n”) |
(“type=cffix” or “type=cfasym”). |
|
You may select the default argument “n” for no |
|
detrending, “c” to demean, or “t” to remove a constant |
|
and linear trend. |
|
You may use the argument “d” to remove drift, if the |
|
option “iorder=1” is also specified. |
|
|
nogain |
Suppresses plotting of the frequency response (gain) |
|
function for fixed length symmetric filters (“type=bk” |
|
or “type=cffix”). By default, EViews will plot the gain |
|
function. |
|
|
noncyc=arg |
Specifies a name for a series to contain the non-cyclical |
|
series (difference between the actual and the filtered |
|
series). If no name is provided, the non-cyclical series |
|
will not be saved in the workfile. |
|
|
230—Appendix B. Command Reference
w=arg |
Store the filter weights as an object with the specified |
|
|
name. For fixed length symmetric filters (“type=bk” or |
|
|
“type=cffix”), the saved object will be a matrix of |
|
|
dimension 1 × ( q + 1 ) where q is the user-specified |
|
|
lag length order. For these filters, the weights on the |
|
|
leads and the lags are the same, so the returned matrix |
|
|
contains only the one-sided weights. The filtered series |
|
|
zt may be computed as: |
|
|
q + 1 |
q + 1 |
|
zt = Σ w( 1, c) yt + 1 − c + Σ w( 1, c) yt + c − 1 |
|
|
c = 1 |
c = 2 |
|
for t = q + 1, …, n − q . |
|
|
For time-varying filters, the weight matrix is of dimen- |
|
|
sion n × n where n is the number of non-missing |
|
|
observations in the current sample. Row r of the |
|
|
matrix contains the weighting vector used to generate |
|
|
the r -th observation of the filtered series, where col- |
|
|
umn c contains the weight on the c -th observation of |
|
|
the original series. The filtered series may be computed |
|
|
as: |
|
|
T |
|
|
zt = Σ w( r, c) yc |
r = 1, …, T |
|
c = 1 |
|
|
where yt is the original series and w( r, c) is the |
|
|
( r, c) element of the weighting matrix. By construc- |
|
|
tion, the first and last rows of the weight matrix will be |
|
|
filled with missing values for the symmetric filter. |
|
|
|
|
p |
Print the graph. |
|
|
|
|
Examples
Suppose we are working in a quarterly workfile and we issue the following command:
lgdp.bpf(type=bk,low=6,high=32) cyc0
EViews will compute the Baxter-King band-pass filter of the series LGDP. The periodicity of cycles extracted ranges from 6 to 32 quarters, and the filtered series will be saved in the workfile in CYC0. The BK filter uses the default lag of 12 (3 years of quarterly data).
Since this is a fixed length filter, EViews will display both a graph of the cyclical/original/ non-cyclical series, as well as the frequency response (gain) graph. To suppress the latter graph, we could enter a command containing the “nogain” option: