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9783540662075

Xplore-Learning Guide: Learning Guide

by ; ;
  • ISBN13:

    9783540662075

  • ISBN10:

    3540662073

  • Format: Paperback
  • Copyright: 1999-12-01
  • Publisher: Springer Verlag
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Summary

This is the comprehensive handbook to XploRe - the interactive statistical environment, a versatile tool for data analysis. XploRe combines classical techniques with high end statistical procedures and is the ideal solution for data exploration. The user-friendly graphics provide an effective basis for large-scale statistical analysis, computer intensive research and interactive knowledge discovery. The open architecture and the Auto Pilot Support System (APSS) guarantees smooth integration of future methods and updated data analysis techniques.

Table of Contents

Preface 15(4)
Part I: First Steps 19(148)
Getting Started
21(22)
Using XploRe
21(8)
Input and Output Windows
21(1)
Simple Computations
22(1)
First Data Analysis
23(1)
Exploring Data
24(3)
Printing Graphics
27(2)
Quantlet Examples
29(5)
Summary Statistics
30(1)
Histograms
30(1)
2D Density Estimation
31(2)
Interactive Kernel Regression
33(1)
Getting Help
34(2)
Basic XploRe Syntax
36(7)
Operators
36(2)
Variables
38(1)
Variable Names
38(1)
Functions
39(1)
Quantlet files
40(3)
Descriptive Statistics
43(26)
Marlene Muller
Data Matrices
43(6)
Creating Data Matrices
44(2)
Loading Data Files
46(1)
Matrix Operations
47(2)
Computing Statistical Characteristics
49(14)
Minimum and Maximum
50(1)
Mean, Variance and Other Moments
51(1)
Median and Quantiles
52(3)
Covariance and Correlation
55(2)
Categorical Data
57(2)
Missing Values and Infinite Values
59(4)
Summarizing Statistical Information
63(6)
Summarizing Metric Data
63(3)
Summarizing Categorical Data
66(3)
Graphics
69(60)
Sigbert Klinke
Basic Plotting
70(9)
Plotting a Data Set
70(1)
Plotting a Function
71(1)
Plotting Several Functions
72(1)
Coloring Data Sets
73(1)
Plotting Lines from Data Sets
74(2)
Several Plots
76(3)
Univariate Graphics
79(11)
Boxplots
80(2)
Dotplots
82(1)
Bar Charts
83(2)
Quantile-Quantile Plots
85(1)
Histograms
86(4)
Multivariate Graphics
90(15)
Three-Dimensional Plots
91(1)
Surface Plots
92(1)
Contour Plots
92(2)
Sunflower Plots
94(1)
Linear Regression
95(2)
Bivariate Plots
97(2)
Star Diagrams
99(1)
Scatter-Plot Matrices
100(2)
Andrews Curves
102(1)
Parallel Coordinate Plots
103(2)
Advanced Graphics
105(4)
Moving and Rotating
105(1)
Simple Predefined Graphic Primitives
106(2)
Color Models
108(1)
Graphic Commands
109(20)
Controlling Data Points
110(1)
Color of Data Points
111(2)
Symbol of Data Points
113(2)
Size of Data Points
115(1)
Connection of Data Points
116(5)
Label of Data Points
121(3)
Title and Axes Labels
124(1)
Axes Layout
125(4)
Regression Methods
129(18)
Jorg Aßmus
Simple Linear Regression
131(6)
Multiple Linear Regression
137(6)
Nonlinear Regression
143(4)
Teachware Quantlets
147(20)
Nathaniel Derby
Visualizing Data
149(1)
Random Sampling
150(3)
The p-Value in Hypothesis Testing
153(2)
Approximating the Binomial by the Normal Distribution
155(2)
The Central Limit Theorem
157(2)
The Pearson Correlation Coefficient
159(3)
Linear Regression
162(5)
Bibliography
165(2)
Part II: Statistical Libraries 167(242)
Smoothing Methods
169(36)
Marlene Muller
Kernel Density Estimation
169(16)
Computational Aspects
171(2)
Computing Kernel Density Estimates
173(3)
Kernel Choice
176(1)
Bandwidth Selection
177(4)
Confidence Intervals and Bands
181(4)
Kernel Regression
185(12)
Computational Aspects
185(1)
Computing Kernel Regression Estimates
186(2)
Bandwidth Selection
188(4)
Confidence Intervals and Bands
192(2)
Local Polynomial Regression and Derivative Estimation
194(3)
Multivariate Density and Regression Functions
197(8)
Computational Aspects
197(1)
Multivariate Density Estimation
197(4)
Multivariate Regression
201(2)
Bibliography
203(2)
Generalized Linear Models
205(24)
Marlene Muller
Estimating GLMs
206(2)
Models
206(2)
Maximum-Likelihood Estimation
208(1)
Computing GLM Estimates
208(7)
Data Preparation
208(1)
Interactive Estimation
209(4)
Noninteractive Estimation
213(2)
Weights & Constraints
215(3)
Prior Weights
216(1)
Replications in Data
217(1)
Constrained Estimation
217(1)
Options
218(3)
Setting Options
219(1)
Weights and Offsets
219(1)
Control Parameters
219(2)
Output Modification
221(1)
Statistical Evaluation and Presentation
221(8)
Statistical Characteristics
221(2)
Output Display
223(1)
Significance of Parameters
223(2)
Likelihood Ratio Tests for Comparing Nested Models
225(1)
Subset Selection
226(2)
Bibliography
228(1)
Neural Networks
229(18)
Wolfgang Hardle
Heiko Lehmann
Feed-Forword Networks
231(1)
Computing a Neural Network
232(4)
Controlling the Parameters of the Neural Network
234(1)
The Resulting Neural Network
235(1)
Running a Neural Network
236(11)
Implementing a Simple Discriminant Analysis
237(4)
Implementing a More Complex Discriminant Analysis
241(5)
Bibliography
246(1)
Time Series
247(26)
Petr Franek
Wolfgang Hardle
Time Domain and Frequency Domain Analysis
247(6)
Autocovariance and Autocorrelation Function
248(3)
The Periodogram and the Spectrum of a Series
251(2)
Linear Models
253(6)
Autoregressive Models
253(1)
Autoregressive Moving Average Models
254(2)
Estimating ARMA Processes
256(3)
Nonlinear Models
259(14)
Several Examples of Nonlinear Models
259(5)
Nonlinearity in the Conditional Second Moments
264(2)
Estimating ARCH Models
266(1)
Testing for ARCH
267(3)
Bibliography
270(3)
Kalman Filtering
273(12)
Petr Franek
State--Space Models
273(4)
Examples of State--Space Models
275(1)
Modeling State--Space Models in XploRe
276(1)
Kalman Filtering and Smoothing
277(3)
Parameter Estimation in State--Space Models
280(5)
Bibliography
283(2)
Finance
285(22)
Stefan Sperlich
Wolfgang Hardle
Outline of the Theory
286(3)
Some History
286(1)
The Black--Scholes Formula
287(2)
Assets
289(5)
Stock Simulation
290(2)
Stock Estimation
292(1)
Stock Estimation and Simulation
292(2)
Options
294(10)
Calculation of Option Prices and Implied Volatilities
294(4)
Option Price Determining Factors
298(3)
Greeks
301(3)
Portfolios and Hedging
304(3)
Calculation of Arbitrage
304(1)
Bull-Call Spreads
305(2)
Microeconometrics and Panel Data
307(46)
Jorg Breitung
Axel Werwatz
Limited-Dependent and Qualitative Dependent Variables
308(12)
Probit, Logit and Tobit
308(2)
Single Index Models
310(1)
Average Derivatives
311(1)
Average Derivative Estimation
312(2)
Weighted Average Derivative Estimation
314(1)
Average Derivatives and Discrete Variables
315(3)
Parametric versus Semiparametric Single Index Models
318(2)
Multiple Index Models
320(4)
Sliced Inverse Regression
321(1)
Testing Parametric Multiple Index Models
322(2)
Self-Selection Models
324(6)
Parametric Model
325(2)
Semiparametric Model
327(3)
Panel Data Analysis
330(13)
The Data Set
333(2)
Time Effects
335(1)
Model Specification
336(2)
Estimation
338(1)
An Example
339(4)
Dynamic Panel Data Models
343(4)
Unit Root Tests for Panel Data
347(6)
Bibliography
349(4)
Extreme Value Analysis
353(22)
Rolf-Dieter Reiss
Michael Thomas
Extreme Value Models
354(2)
Generalized Pareto Distributions
356(2)
Assessing the Adequacy: Mean Excess Functions
358(1)
Estimation in EV Models
359(2)
Linear Combination of Rations of Spacings (LRS)
359(1)
ML Estimator in the EV Model
360(1)
ML Estimator in the Gumbel Model
360(1)
Fitting GP Distributions to the Upper Tail
361(1)
Parametric Estimators for GP Models
362(6)
Moment Estimator
363(1)
ML Estimator in the GP Model
364(1)
Pickands Estimator
364(1)
Drees--Pickands Estimator
365(1)
Hill Estimator
366(1)
ML Estimator for Exponential Distributions
366(1)
Selecting a Threshold by Means of a Diagram
367(1)
Graphical User Interface
368(1)
Example
369(6)
Bibliography
373(2)
Wavelets
375(34)
Yuri Golubev
Wolfgang Hardle
Zdenek Hlavka
Sigbert Klinke
Michael H. Neumann
Stefan Sperlich
Quantlib twave
377(4)
Change Basis
378(1)
Change Function
379(1)
Change View
380(1)
Discrete Wavelet Transform
381(2)
Function Approximation
383(2)
Data Compression
385(3)
Two Sines
388(1)
Frequency Shift
389(3)
Thresholding
392(10)
Hard Thresholding
393(2)
Soft Thresholding
395(2)
Adaptive Thresholding
397(5)
Translation Invariance
402(2)
Image Denoising
404(5)
Bibliography
407(2)
Part III: Programming 409(94)
Reading and Writing Data
411(18)
Sigbert Klinke
Jurgen Symanzik
Marlene Muller
Reading and Writing Data Files
411(3)
Input Format Strings
414(3)
Output Format Strings
417(2)
Customizing the Output Window
419(10)
Headline Style
421(1)
Layer Style
422(2)
Line Number Style
424(1)
Value Formats and Lengths
425(1)
Saving Output to a File
426(3)
Matrix Handling
429(36)
Yasemin Boztug
Marlene Muller
Basic Operations
429(11)
Creating Matrices and Arrays
430(5)
Operators for Numeric Matrices
435(5)
Comparison Operators
440(2)
Matrix Manipulation
442(6)
Extraction of Elements
442(3)
Matrix Transformation
445(3)
Sums and Products
448(2)
Distance function
450(1)
Decompositions
451(6)
Spectral Decomposition
451(3)
Singular Value Decomposition
454(1)
LU Decomposition
455(1)
Cholesky Decomposition
456(1)
Lists
457(8)
Creating Lists
457(2)
Handling Lists
459(3)
Getting Information on Lists
462(3)
Quantlets and Quantlibs
465(38)
Wolfgang Hardle
Zdenek Hlavka
Sigbert Klinke
Quantlets
465(11)
Flow Control
476(12)
Local and Global Variables
476(2)
Conditioning
478(2)
Branching
480(1)
While-Loop
481(1)
Do-Loop
482(1)
Optional Input and Output in Procedures
483(3)
Errors and Warnings
486(2)
User Interaction
488(7)
APSS
495(4)
Quantlibs
499(4)
Appendix 503(13)
A Customizing XploRe
505(4)
A.1 XploRe.ini
505(1)
A.1.1 The ini File
505(2)
A.1.2 Composing Paths
507(1)
A.2 startup.xpl
508(1)
B Data Sets
509(7)
B.1 Netincome--Food Expenditures
509(1)
B.2 U.S. Companies
509(1)
B.3 CPS 1985
510(1)
B.4 Boston Housing
510(1)
B.5 Lizard Data
511(1)
B.6 Kyphosis Data
512(1)
B.7 Swiss Bank Notes
513(1)
B.8 Earnings Data
513(1)
B.9 Westwood Data
514(1)
B.10 Pullover Data
514(1)
B.11 Geyser Data
514(1)
Bibliography
515(1)
Index 516

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