second edition

wolfgang

这么经典的东西竟然没人下载。。。。。。。。。。。

Wolfgang H?rdle · Léopold Simar
Applied Multivariate Statistica lAnalysis
Wol fgang H?rdle

Humboldt-Universit?t zu Berlin
CASE - Center for Applied Statistics and Economics
Institut für Statistik und ?konometrie
Spandauer Stra?e 1
10178 Berlin, Germany
e-mail: haerdle@wiwi.hu-berlin.de
Léopold Simar
Université Catholique Louvain
Inst. Statistique
voie du Roman Payas 20
1348 Louvain-la-Neuve, Belgium
e-mail: simar@stat.ucl.ac.be


SPRINGER 好似论坛早已有了，大家可以搜搜。

Preface to the 2nd Edition
The second edition of this book widens the scope of the methods and applications of Applied
Multivariate Statistical Analysis. We have introduced more up to date data sets in our
examples. These give the text a higher degree of timeliness and add an even more applied
?avour. Since multivariate statistical methods are heavily used in quantitative ?nance and
risk management we have put more weight on the presentation of distributions and their
densities.
We discuss in detail di?erent families of heavy tailed distributions (Laplace, Generalized Hy-
perbolic). We also devoted a section on copulae, a new concept of dependency used in the
?nancial risk management and credit scoring. In the chapter on computer intensive meth-
ods we have added support vector machines, a new classi?cation technique from statistical
learning theory. We apply this method to bankruptcy and rating analysis of ?rms. The very
important CART (Classi?cation and Regression Tree) technique is also now inserted into
this chapter. We give an application to rating of companies.


我就是好久好久之前从人大经济论坛下载的，这是第二版的说明。

终于碰到懂得人了，这么好的书竟然没人下载，难道没有人看外文的书籍的？

1 Comparison of Batches
Multivariate statistical analysis is concerned with analyzing and understanding data in high
dimensions. We suppose that we are given a set {xi}n
i=1 of n observations of a variable vector
X in Rp. That is, we suppose that each observation xi has p dimensions:
xi = (xi1, xi2, ..., xip),
and that it is an observed value of a variable vector X ∈ Rp. Therefore, X is composed of p
random variables:
X = (X1,X2, ...,Xp)
where Xj, for j = 1, . . . , p, is a one-dimensional random variable. How do we begin to
analyze this kind of data? Before we investigate questions on what inferences we can reach
from the data, we should think about how to look at the data. This involves descriptive
techniques. Questions that we could answer by descriptive techniques are:
 Are there components of X that are more spread out than others?
 Are there some elements of X that indicate subgroups of the data?
 Are there outliers in the components of X?
 How “normal” is the distribution of the data?
 Are there “low-dimensional” linear combinations of X that show “non-normal” behavior?
One difficulty of descriptive methods for high dimensional data is the human perceptional
system. Point clouds in two dimensions are easy to understand and to interpret. With
modern interactive computing techniques we have the possibility to see real time 3D rotations
and thus to perceive also three-dimensional data. A “sliding technique” as described in
H¨ardle and Scott (1992) may give insight into four-dimensional structures by presenting
dynamic 3D density contours as the fourth variable is changed over its range.
A qualitative jump in presentation difficulties occurs for dimensions greater than or equal to
5, unless the high-dimensional structure can be mapped into lower-dimensional components
Klinke and Polzehl (1995). Features like clustered subgroups or outliers, however, can be
detected using a purely graphical analysis.
In this chapter, we investigate the basic descriptive and graphical techniques allowing simple
exploratory data analysis. We begin the exploration of a data set using boxplots. A boxplot
is a simple univariate device that detects outliers component by component and that can
compare distributions of the data among different groups. Next several multivariate techniques
are introduced (Flury faces, Andrews’ curves and parallel coordinate plots) which
provide graphical

我贴出来第一章，就是这种可以复制下来的版本，打印出来很漂亮，看着也舒服，绝对不是那种扫描仪扫出来东一块黑西一块白的东西。，，，，，，，，

ps：可能有点贵，但是这个版我是死缠烂打才要到的，一般的人拿不到这个版本的

不是碰到懂得人乐，是碰到已经下载过的人乐。

都说不同版本了，5个论坛币就能拿到一个清晰地版本，我个人觉得还是很值得的

继续顶起来

有谁下载了，我们可以讨论一下~

好贵阿，有什么比较简单赚钱的方法吗

这样一本书5个论坛币还贵。。。。。。。。

小弟也是穷人，经常下载搞到自己快破产

自己顶一下，如果大家觉得好，请留言，我还有很多类似的资料，都可以放上来

this document is damaged
content is invisible
pay me back!

这是第二版，当前又第6版了。

不错，多谢分享！

这个是最新版本，2015版  要的带走

以上2015版的下载后已损坏，无法打开！

以上2015版的下载后已损坏，无法打开！

很长没来，私信邮箱有时间发给你

高清，支持一下。。。。

没有编程成一个文件，阅读起来不是很方便，建议编辑成一个文件

好书，下载了，谢谢！

感谢分享