- print
- 1.1.5
- pi
- 1.4.3
- eh
- 1.4.3
- adaptive thresholding
- 14.7.3
- ADE
- 12.1.3
- weighted
- 12.1.5
- alphanumeric matrix
- 2.1.1
| 16.1.1
- Andrews curves
- 3.3.9
- ANOVA table
- 4.1
- APSS
- 1.3
| 17.4
- ARCH model
- 9.3.2
- estimation
- 9.3.3
- testing
- 9.3.4
- ARMA process
- 9.2.3
- ASCII data
- 15.1
| 15.2
- Asset Price
- 11.1
- autocorrelation
- 9.1.1
- autocovariance
- 9.1.1
- autoregressive process
- 9.2.1
- average derivative estimation
- see ADE
- balanced panel
- 12.4
- bandwidth selection
- density estimation
- 6.1.4
- kernel regression
- 6.2.3
- bar chart
- 3.2.3
- Bitmap file
- 1.1.5
- Black Scholes
- 11.2
- boxplot
- 3.2.1
- categorical data
- 2.2.5
- central limit theorem
- teachware
- 5.5
-test of independence
- 2.3.2
- Cholesky decomposition
- 16.6.4
- color models
- RGB and HLS
- 3.4.3
- colors
- 3.5.1
| 3.5.2
- columns
- 2.1.3
| 16.3.1
- components
- see list
- composed object
- see list
- concatenation operator
- 2.1.1
| 16.1.1
- conditional heteroscedasticity
- 9.3.2
- conditional logit model
- 12.2.2
- confidence bands
- kernel smoothing
- 6.1.5
| 6.2.4
- confidence intervals
- kernel smoothing
- 6.1.5
| 6.2.4
- constraints
- GLM
- 7.3.3
- contingency table
- 2.3.2
- contour plots
- 2D graphics
- 3.3.3
- 3D graphics
- 3.3.3
- correlation
- matrix
- 2.2.4
- teachware
- 5.6
- covariance
- coefficient
- 2.2.4
- matrix
- 2.2.4
- cross table
- 2.3.2
- cumulative product
- 16.4
- cumulative sum
- 16.4
- data
- categorical
- 2.2.5
- matrix
- 2.1
| 16.1.1
- data files
- dimension
- 2.1.3
| 16.1.1
- read
- 2.1.2
| 15.
- write
- 15.
- data matrix
- 2.1
- create
- 2.1.1
| 16.1.1
- data sets
- B.
- data visualization
- teachware
- 5.1
- density function
- estimation
- 6.1
- derivative function estimation
- 6.2.5
- descriptive statistics
- 2.
- determinant
- 16.1.2
- diagonal matrix
- 16.1.1
- discrete wavelet transform
- 14.2
- display
- 3.1
- distance
- 16.5
- do-loop
- 17.2.5
- dotplot
- 3.2.2
- Drees-Pickands estimator
- 13.6.4
- dynamic panel model
- 12.5
- effective dimension reduction
- 12.2.1
- eigenvalues
- 16.6.1
- eigenvectors
- 16.6.1
- elements
- list
- 16.7.1
- matrix
- 16.3.1
- empirical moments
- 2.2.2
- empirical wavelet coefficients
- 14.5
- environment variables
- 15.4
| A.1.1
- error message
- 17.2.7
- exponential distributions
- 13.6.6
- extraction of elements
- 16.3.1
- extreme value models
- 13.1
- fixed effects model
- panel data
- 12.4
- format string
- 15.3
- Fourier series
- wavelets
- Overview
- frequency
- 2.2.5
- table
- 2.3.2
- frequency domain
- 9.1
- GARCH model
- 9.3.2
- generalized linear models
- see GLM
- generalized Pareto distribution
- 13.2
- GLM
- 7.
- distributions
- 7.1.1
- estimation
- 7.1
- interactive estimation
- 7.2.2
- maximum-likelihood
- 7.1.2
- noninteractive estimation
- 7.2.3
- output display
- 7.5.2
- global variables
- 17.2.1
- GMM estimation
- panel data
- 12.5
- graphical primitives
- 3.4.2
- graphics
- 2D
- 3.3.6
- 3D graphics
- 3.3.1
- mask commands
- 3.5
- move and rotate
- 3.4.1
- multivariate
- 3.3
- univariate
- 3.2
- Greeks
- 11.4
- grid
- 3.1.2
- Gumbel model
- 13.4.3
- hard thresholding
- 14.7.1
- Hausman test
- panel data
- 12.4.3
- help file
- 17.4
- help system
- see APSS
| A.1.1
- Hill estimator
- 13.6.5
- histogram
- 3.2.5
- HTML help file
- 17.4
- hypothesis testing
- teachware
- 5.3
- if-branch
- 17.2.2
- image denoising
- 14.9
- Impled Volatility
- 11.5
- individual effects
- panel data
- 12.4
- infinite values
- 2.2.6
- input window
- 1.1.1
- inverse matrix
- 16.1.2
- inverse regression
- 12.2.1
- kernel density estimation
- 6.1
| 6.1.2
- kernel function
- 6.1
- kernel regression
- 1.2.4
| 6.2
| 6.2.2
| 17.3
- kernel smoothing
- 6.
- bandwidth selection
- 6.1.4
| 6.2.3
- computational aspects
- 6.1.1
| 6.2.1
| 6.3.1
- confidence bands
- 6.1.5
| 6.2.4
- confidence intervals
- 6.1.5
| 6.2.4
- density estimation
- 6.1
| 6.1.2
- kernel choice
- 6.1.3
- local polynomial regression
- 6.2.5
- multivariate
- 6.3
- multivariate density estimation
- 6.3.2
- multivariate regression
- 6.3.3
- regression
- 6.2
| 6.2.2
- kurtosis
- 2.2.2
- labels
- 3.5.6
- least squares regression
- 4.1
- library
- 17.
- likelihood ratio test
- GLM
- 7.5.4
- line
- 3.1
- linear regression
- 3.3.5
| 4.1
- model selection
- 4.2
- multiple
- 4.2
- simple
- 4.1
- teachware
- 5.7
- lines
- 3.5.5
- link function
- 7.
- canonical
- 7.1.1
- list
- 16.7
- components
- 16.7.1
| 16.7.3
- create
- 16.7.1
- elements
- 16.7.1
- manipulate
- 16.7.2
- local polynomial regression
- 6.2.5
- local variables
- 17.2.1
- logical operators
- 16.2
- logit model
- 7.
| 12.1.1
- conditional
- 12.2.2
- multinomial
- 12.2.2
- loop
- 17.2.4
| 17.2.5
- LRS
- 13.4.1
- LU decomposition
- 16.6.3
- matrix
- 16.
- decomposition
- 16.6
- elements
- 16.3.1
- reshape
- 16.3.2
- matrix operations
- 2.1.3
| 16.1.2
- maximum
- 2.2.1
- mean
- 2.2.2
- mean excess function
- 13.3
| 13.8
- median
- 2.2.3
- minimum
- 2.2.1
- missing values
- 2.2.6
- model selection
- GLM
- 7.5.4
- linear regression
- 4.2
| 4.2
- moment estimator
- 13.6.1
- moving average process
- 9.2.2
- multinomial logit model
- 12.2.2
- multiresolution analysis
- 14.3
- multivariate
- 14.9
- nonlinear regression
- 4.3
- normal approximation
- teachware
- 5.4
- operators
- logical
- 16.2
- numeric
- 16.1.2
- optional parameters
- GLM
- 7.4
- procedures
- 17.2.6
- output
- format string
- 15.3
- GLM
- 7.5.2
- output window
- 1.1.1
- customizing
- 15.4
- format data
- 15.4.4
- save to file
- 15.4.5
- panel data
- 12.4
- parallel coordinate plot
- 3.3.10
- Pareto distribution
- 13.2
- periodogram
- 9.1.2
i
- 1.4.3
- Pickands estimator
- 13.6.3
- plot
- 3.1
- colored lines
- 3.1.5
- colored points
- 3.1.4
- data
- 3.1.1
- function
- 3.1.2
- several functions
- 3.1.3
- several plots
- 3.1.6
- plots
- axes
- 3.5.7
| 3.5.8
- title
- 3.5.7
- PostScript file
- 1.1.5
- principal components
- 3.3.6
- print graphics
- 1.1.5
- probit model
- 7.
| 12.1.1
- procedure
- 17.1
| 17.1
- product
- 16.4
- matrix
- 16.1.2
- program
- 17.
- programming
- conditional branches
- 17.2.2
- procedure
- 17.1
- variables
- 17.2.1
- pseudorandom numbers
- 16.1.1
- QQ-plot
- 3.2.4
- GP
- 13.6.1
- quantile
- 2.2.3
- quantlet
- 17.
| 17.
- quantlib
- 17.
| 17.5
- random effects model
- panel data
- 12.4
- random numbers
- 16.1.1
- random sampling
- teachware
- 5.2
- read
- ASCII data
- 15.2
- data files
- 2.1.2
| 15.
| 15.1
- regression
- estimation
- 4.
| 6.2
- replications
- GLM
- 7.3.2
- rows
- 2.1.3
| 16.3.1
- sample selection
- 12.3
- scatter plot
- 3.1.1
- scatter-plot matrix
- 3.3.8
- seed
- 16.1.1
- selection of elements
- 16.3.1
- self-selection
- 12.3
- SIM
- 12.1.2
- misspecification test
- 12.1.7
- single index models
- see SIM
- singular value decomposition
- 16.6.2
- SIR
- 12.2.1
- skewness
- 2.2.2
- sliced inverse regression
- see SIR
- smoothing methods
- 6.
- soft thresholding
- 14.7.2
- sort
- 16.3.1
- spectral decomposition
- 16.6.1
- standard deviation
- 2.2.2
- star diagram
- 3.3.7
- statistical characteristics
- 2.2
- GLM
- 7.5.1
- string matrix
- 2.1.1
| 16.1.1
- subset selection
- GLM
- 7.5.5
- linear regression
- 4.2
- subwindows
- 3.1.6
- sum
- 16.4
- matrix
- 16.1.2
- sum of squares
- 4.1
- summary statistics
- 2.3
- categorical data
- 2.3.2
- metric data
- 2.3.1
- sunflower plot
- 3.3.4
- surfaces
- 3D graphics
- 3.3.2
- switch statement
- 17.2.3
- symbol sizes
- 3.5.4
- symbols
- 3.5.1
| 3.5.3
-test
- GLM
- 7.5.3
- linear regression
- 4.2
- tail fitting
- 13.5
| 13.6.7
- teachware
- central limit theorem
- 5.5
- correlation
- 5.6
- data visualization
- 5.1
- hypothesis testing
- 5.3
- linear regression
- 5.7
- normal approximation
- 5.4
- random sampling
- 5.2
- text matrix
- 2.1.1
| 16.1.1
- The Binomial pricing model
- 11.3
- thresholding
- 14.7
- adaptive
- 14.7.3
- hard
- 14.7.1
- soft
- 14.7.2
- time domain
- 9.1
- time effects
- panel data
- 12.4.2
- time series
- 9.
- ARMA models
- 9.2.2
- autoregressive process
- 9.2.1
- linear models
- 9.2
- nonlinear models
- 9.3
- periodogram
- 9.1.2
- tobit model
- 12.1.1
- transpose
- 16.1.2
- unit matrix
- 16.1.1
- unit root test
- panel data
- 12.6
- variables
- 17.2.1
- existence
- 17.2.6
- local and global
- 17.2.1
- variance
- 2.2.2
- warning message
- 17.2.7
- wavelet coefficients
- 14.5
| 14.6
| 14.7
- wavelet estimators
- 14.8
- wavelet transform
- 14.7
- wavelets
- 14.
- basis
- 14.1.1
- data compression
- 14.4
- father wavelet
- 14.3
- frequency shift
- 14.6
- mother wavelet
- 14.3
- resolution scale
- 14.6
- thresholding
- 14.4
| 14.7
- wavelet transform
- Overview
- weighted average derivative
- 12.1.5
- weights
- GLM
- 7.3
- while-loop
- 17.2.4
- write
- data files
- 15.1
- formatted data
- 15.3
- output window
- 15.4.5
- WWW help system
- A.1.1
- XploRe.ini
- A.1