Data Structures for Computational Statistics

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Springer Science & Business Media, May 20, 1997 - Business & Economics - 284 pages
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Since the beginning of the seventies computer hardware is available to use programmable computers for various tasks. During the nineties the hardware has developed from the big main frames to personal workstations. Nowadays it is not only the hardware which is much more powerful, but workstations can do much more work than a main frame, compared to the seventies. In parallel we find a specialization in the software. Languages like COBOL for business orientated programming or Fortran for scientific computing only marked the beginning. The introduction of personal computers in the eighties gave new impulses for even further development, already at the beginning of the seven ties some special languages like SAS or SPSS were available for statisticians. Now that personal computers have become very popular the number of pro grams start to explode. Today we will find a wide variety of programs for almost any statistical purpose (Koch & Haag 1995).
 

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Contents

Introduction
1
12 The Need of Interactive Environments
4
13 Modern Computer Soft and Hardware
18
Exploratory Statistical Techniques
25
22 Some Stratifications
28
23 Boxplots
29
24 QuantileQuantile Plot
31
25 Histograms Regressograms and Charts
33
46 Requirements for a Tool Doing Exploratory Projection Pursuit
166
Data Structures
169
52 For Data Objects
173
53 For Linking
181
54 Existing Computational Environments
187
Implementation in XploRe
197
62 Selected Commands in XploRe 32
210
63 Selected Tools in XploRe 32
217

26 Bivariate Plots
40
27 Scatterplot Matrices
46
28 Three Dimensional Plots
48
29 Higher Dimensional Plots
52
210 Basic Properties for Graphical Windows
58
Some Statistical Applications
61
32 Teachware
69
33 Regression Methods
72
Exploratory Projection Pursuit
91
42 The Basis of Exploratory Projection Pursuit
102
43 Application to the Swiss Banknote Dataset
145
44 Multivariate Exploratory Projection Pursuit
148
45 Discrete Exploratory Projection Pursuit
162
64 Data Structure in XploRe 40
233
65 Commands and Macros in XploRe 40
237
Conclusion
239
The Datasets
241
A2 Berlin Housing Data and Berlin Flat Data
242
A3 Swiss Banknote Data
245
Mean Squared Error of the FriedmanTukey Index
247
Density Estimation on Hexagonal Bins
257
Programs
263
D2 Mathematica Program
266
Tables
269
References
277
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