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향상된
성능 및 능력
• 비선형 추정, 모형
해법, 그리고 시리즈 표현의 평가를 포함하는 기타 연산(operations)이 더욱 빨라졌습니다.
• Windows
XP, Vista, 64-Bit XP 또는 Vista에서 사용 가능하며, EViews 5.1에서 보다
1.5 배 정도의 큰 데이터를 다룰 수 있게 되었습니다.
통계학
및 계량경제학 기능들
Statistics
• EViews 6 features
a new factor analysis object that allows you to: (1) compute
covariances, correlations, or other measure of association
(if necessary), (2) specify the number of factors, (3) obtain
initial uniqueness estimates, (4) extract (estimate) factor
loadings and uniquenesses, (5) examine diagnostics, (5)
perform factor rotation, (6) estimate factor scores.
You may select from
a menu of automatic methods for choosing the number of factors
to be retained, or you may specify an arbitrary number of
factors. You may estimate your model using principal factors,
iterated principal factors, maximum likelihood, unweighted
least squares, generalized least squares, and noniterative
partitioned covariance estimation (PACE). Once you obtain
initial estimates, rotations may be performed using any
of more than 30 orthogonal and oblique methods, and factor
scores may be estimated in more than a dozen ways.
• Principal
components analysis in EViews 6 has been greatly enhanced.
You may now display line graphs of the ordered eigenvalues
(scree plots), and examine scatterplots of the loadings
and component scores (biplots). Loadings and component scores
may now be computed with various weightings so that you
may, for example, construct orthonormal or eigenvalue matching
scores.
• In addition
to the previously supported ordinary (Pearson) correlations
and covariances, you may now compute alternative measures
of association: Spearman rank-order, Kendall's tau-a and
tau-b, as well as partial correlations and covariances.
EViews 6 now performs pairwise tests of zero correlation,
with or without multiple comparison adjustments.
• Mean equality
tests (ANOVA) now perform tests both under the standard
maintained assumption of equal variances across subgroups,
and now, under the assumption that the variances are heteroskedastic
(Welch 1951, Satterthwaite 1946).
Econometrics
General
• Linear
quantile regression and least absolute deviations (LAD)
specifications (Koenker, 2005) may now be estimated. Asymptotic
covariance matrices for the quantile regression estimates
may be calculated assuming i.i.d. errors, Huber's
Sandwich, or bootstrap methods. Specialized tools permit
you to test for slope equality across quantile estimates
(Koenker and Bassett, 1982), or to test for symmetry across
quantile estimates (Newey and Powell, 1987).
• EViews 6 provides
stepwise regression tools for variable selection in ordinary
least squares models. Among the methods and criteria that
EViews supports are: undirectional-forwards, uni-directional-backwards,
stepwise-forwards, stepwise-backwards, swapwise-max R-squared
increment, and combinatorial.
• EViews 6 offers
expanded heteroskedasticity testing (including Breusch-Pagan
(1979), Godfrey (1978), Harvey (1978), Glejser (1969)),
as well as the ability to specify custom tests in which
you can test against departures from the homoskedastic null
in a number of directions (say, by combining a White and
Harvey test).
• EViews 6 now
offers the Quandt-Andrews Breakpoint Test (Andrews, 1993
and Andrews and Ploberger, 1994) which tests for one or
more unknown structural breakpoints in an equation's sample.
• The Binary,
Count, Censored, and Ordered equation estimation methods
now permit you to specify your equation by expression (instead
of restricting you to providing a list). This flexibility
allows you to construct non-linear index specifications,
or models with coefficient restrictions.
Time-series
• You
may now perform cointegration tests with panel and pooled
time series cross-section data using the panel cointegration
statistics of Pedroni (2004), Pedroni (1999), and Kao (1999),
or the Fisher-type test suggested by Maddala and Wu (1999).
• EViews
now estimates multivariate GARCH models, providing support
for the most popular multivariate specifications: Conditional
Constant Correlation, the Diagonal VECH and (indirectly)
the Diagonal BEKK. You may estimate the model assuming multivariate
normal or multivariate t-distribution errors. Once estimated,
you may examine the fitted conditional covariances, variances,
and correlations and save results to your workfile. In addition,
you may perform residuals tests on the raw or standardized
residuals, where the latter may be computed using various
standardization methods.
• EViews
6 allows you to estimate integrated univariate GARCH models,
constraining the persistent parameters of GARCH model to
sum up to unity. The constant term in a GARCH model can
be restricted, or the variance targeted, so that the long
run variance of the model equals to the sample variance
of the data. Users may now choose the weight when backcasting
is used to calculate the pre-sample variance.
그래픽
기능들
We have completely
revamped our graphics engine, allowing you greater control
over the display of data, and supporting the construction
of categorical graphs.
Basic Features
• New basic
graph types: Dot plot, Area Band.
• Graphs may
easily be displayed for summary statistics of your data
(e.g., showing a bar graph of the mean values of
each series in a group).
• Histograms,
boxplots, or kernel density graphs may be displayed in the
margins of observation (line, bar, scatter, etc.)
graphs.
• EViews 6 offers
a number of new univariate statistical graphs: histograms
with options for controlling bins, frequency polygons, histogram
edge polygons, average shifted histograms, fitted theoretical
distribution plots (e.g., a normal density fit to
sample data), empirical log survivor plots, confidence ellipses.
• In addition,
statistical graphs may now be overlaid on other graphs so
that you may, for example, draw a kernel density and fitted
normal distribution graph on top of a histogram, or you
can overlay both a fitted linear regression line and a kernel
regression plot on top of a scatterplot.
• EViews 6 now
supports line graphs containing mixed frequency data.
• You
may now save EViews graph output in .bmp, .gif, .png, and
.jpg formats.
Categorical Graph Tools
Categorical graph
tools allow you to construct observation or analytical graphs
formed using various subsets of the data, where the subsets
are defined using the values of one or more categorical
conditioning variables. Using these tools, you may quickly
and easily perform complex tasks such as:
• Displaying
a bar plot comparing the mean incomes of individuals living
in each state.
• Producing
a scatterplot of wages and hours worked, where the subset
of males is drawn using one plotting symbol, and the subset
of females uses a different symbol.
• Showing wage-education
profiles for both male and female workers.
• Drawing histograms
and boxplots of wages for union and non-union workers in
different industries.
Customization Tools
• Data may now
be assigned to any axis (including bottom and top). Among
other things, this allows you to produce rotated graphs.
• EViews 6 supports
character labeling of axis using the workfile structure,
with optional rotation of the label.
• You may now
specify custom label elements for axes in frozen graphs.
• You may now
apply fade effects to fill colors in bars and backgrounds
Output
Management
• EViews 6 offers
a new spool object that allows you to create collections
of various EViews output. The EViews spool object is essentially
a container that allows you to store multiple tables, graphs,
text, and spools. Various management tools allow you to
add, delete, extract, resize, annotate, hide and edit the
objects in the spool.
You may find
spools to be useful for organizing results, for example
for creating a log of the results for a project or an EViews
session, or perhaps for gathering output for a presentation.
모형들(Models)
EViews 6 model solution
may be up to 30 times faster than under EViews 5.1. Among
the improvements:
• A new solution
algorithm has been added to models. Broyden's method is
a quasi-Newton method that uses a secant approximation to
the Jacobian instead of the true Jacobian when solving for
the Newton step. The method has many of the desirable properties
of Newton's method without requiring the Jacobian to be
evaluated and factored at each step.
• The model
solver can now reorder equations within simultaneous blocks
so that a set of variables in the block can be solved recursively,
conditional on the values of the remaining variables in
the block. This structure is used by the Newton and Broyden
solution algorithms to substantially reduce the time required
to solve models consisting of large sparse systems of equations.
• Stochastic
simulations can now be based on bootstrapped residuals as
an alternative to normally distributed random numbers. Bootstrapped
residuals may be drawn independently for each equation,
or may be drawn from the same period across all equations.
• The complete
set of results from each repetition of a stochastic simulation
can now be saved as a new page in the workfile.
• Equations
for endogenous variables can now be excluded from the model
(treated as exogenous variables) automatically based on
whether actual values are available for the variable in
each period. This makes it easy to perform forecasts using
all available data when some series may be obtained more
quickly than others.
데이터베이스
• Support has
been added for direct access from within EViews to databases
from Datastream (a service of Thomson Financial), Moody's
Economy.Com and FactSet, for users who are subscribers to
these services. (Enterprise edition only.)
• Series imported
into workfiles from a database can now maintain a link to
the source database, allowing the data to be refreshed from
the database each time the workfile is opened, or upon user
request.
기타
• EViews 6 provides
over 100 new series expression functions, including new
sets of functions for moving statistics (e.g., @movstdev),
cumulative statistics (e.g., @cumstdev), and statistics
on the rows of a group (e.g., @rmean, which computes
the mean across the series in the group), financial calculations
(various present value and rate calculations), ranks, and
maximum likelihood and unbiased variance calculations.
• New matrix
language functions for various element operations (matrix
element multiply divide, power), and for row and column
scaling.
• Series classification
tools allow you to create classification variables based
on the values in a series. You may use this to create custom
"binning" of series, for example, using an income
series to group observations into categories using a grid
of income values, marginal tax brackets, or quantiles of
income.
• New
functions allow you to start the Windows command shell or
to spawn a process from within EViews.
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