Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

## Statistical Data Analysis

### Basic Statistics

aseq
cov
Computes the covariance structure of a given array.
max
max computes the maximal value of the elements of an array regarding a given dimension.
maxind
maxind gives a row vector with the index of the maximum element in each column of a matrix. As usally this functionality extends to higher dimensional arrays.
mean
mean computes the mean of the elements of an array regarding a given dimension.
median
Computes the empirical medians of a given array.
min
min computes the minimum value of the elements of an array regarding a given dimension.
minind
minind gives a row vector with the index of the minimum element in each column of a matrix. As usally this functionality extends to higher dimensional arrays.
mseq
Computes a multiplicative sequence.
var
var computes the variance of the elements of an array regarding a given dimension.

### Graphical User Interfac

readevent reads a key- or a mouse- event while a program is running. An "event" is a stroke of a key or a click of a mouse button. readevent will be mainly useful for letting XploRe know whether such an event has occured and to get some special information like the coordinates where the mouse click

### Nonparametric Methods

isoreg
isoreg computes the isotonic regression smoother via the Pool Adjacent Violators algorithm. Given a data set {(X_i,Y_i)} where X_i <= X_(i+1) i=1,...,n finds the values {mhat(X_i)} i=1,...,n, such that, minimizes (1/n) sum_i=1,...,n [Y_i - mhat(X_i)]^2 subject to mhat(X_i) <= mhat[X_(i+1)], i=
l1line
l1line computes the least absolute deviation line from scatterplot data. It gives the estimate b0 and b1 that minimizes sum_i=1,n |y_i - b0 - b1 x_i |.
locpol
locpol computes the local polynomial estimator. It is using the quartic kernel.
locpoldis
locpoldis computes the local polynomial estimator without mixed terms but allows for including a linear part in the regression model. It is using the quartic kernel.
lowess
lowess computes the robust locally weighted regression. Fitted values are computed at each of the given values x.
rmed
rmed computes the running median of y using the optimal median smoothing algorithm of Haerdle and Steiger (1990).
sker
sker computes a direct kernel estimate without binning from scatter plot data.
sknn
sknn computes the k-nearest neighbour smooth regression from scatter plot data. As inputs you have to specify the explanatory variable x, the dependent variable y and the smoothing parameter k.
spline
spline fits a cubic spline to input data.

Keywords - Function Groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

 (C) MD*TECH Method and Data Technologies, 05.02.2006 Impressum