[下载]EViesw 6.0 正式版光盘镜像，免费和大家共享。请求置顶

感谢、祝福和期待。

搂住辛苦了，谢谢。

要求版主置顶

谢谢楼主!怎么解压和安装啊?

期待英特纳雄耐尔的出现！！！

EViews 6版本功能更新
EViews 6 features a wide range of exciting changes and improvements. The
following is a brief summary of some of the most important new features in
Version 6.
Improved Performance & Capacity
Nonlinear estimation, model solution, and other operations involving
evaluation of series expressions are significantly faster since EViews now
compiles expressions to native machine code.
Using Windows XP with the 3G switch, Vista, or 64-bit XP or Vista, data
capacity can be up to two and one-half times as large as under EViews 5.1.
Statistics and Econometrics Features
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 suppported 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.

Graphics
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.
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 for 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.
Databases
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.
Miscellaneous
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.

大家有下下来的吗？为什么我下来解压后是蒙特卡罗方法的课件

[此贴子已经被作者于2007-6-2 16:15:39编辑过]

thanks