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

abinfonewton - adddata - agglom - append - asinh - axeson
abinfonewton Auxiliary routine for rICfil: solves - if possible - by explicit integration and Newton-Algorithm E [|AX|^2 \min{1,b/|AX|}]=1, E [|AX|^2 \min{1,b^2/|AX|^2}]=(1+e)p for X ~ N_p (0,unit(p))
abs Computes the absolute values of the elements of an array.
absepnewton Auxiliary routine for rICfil: solves - if possible - by explicit integration and Newton-Algorithm (separate clipping in 1 dimension of normal scores X=X1+X2, X1,X2 indep.)

E [A (X1 \min{1,b/|AX1|} +X2) (X1+X2) ]=1,

E [A^2 (X1 \min{1,b/|AX1|} +X2)^2]=(1+e) /(S1+S2)

for X=X1+X2, X1 ~ N(0,S1), X2 ~ N(0,S2) indep1

acf computes the autocorrelation function for time series
acfplot plots the autocorrelation function of a time series.
acos Returns the arccosine of the elements of an array.
acosh Returns the inverse hyperbolic cosine of the elements of an array.
adap performs an adaptive K-means cluster analysis
adaptive performs an adaptive K-means cluster analysis with appropriate (adaptive) multivariate graphic using the principal components
addbutton Adds a button with some functionality to the plot menu.

adddata Adds graphics to already plotted ones.

addfnci auxiliary quantlet for cointegration
addlist Adds components to an existing list or creates a new list with specific components.
addr creates one hidden layer network
adedis adedis computes estimates of the slope coefficients in a single index model. The coefficents of the continuous variables are estimated by (an average of) dwade (density-weighted average derivtive) estimates. The coefficients of the disrete explanatory variables are estimated by the method proposed in Horowitz and Haerdle, JASA 1996.
adeind indirect average derivative estimation using binning
adeslp slope estimation of average derivatives using binning
adf Calculation of the two tabulated testvalues (the general one is tau) for the Augmented Dickey-Fuller Test of a unit root in an autoregressive process for with a constant. If the third argument is "trend" a linear trend is calculated. The third return value is a vector of critical values for tau.
aerlb computes the Lachenbruch-Mickey unbiased estimate of the actual discrimination error rate
agen auxiliary quantlet for VAR models
agglom performs hierarchical cluster analysis.
american starting program to calculate option prices for american options
anaabl
andrews andrews calculates the semiparametric estimator proposed by Andrews and Schafgans (1994) of the intercept coefficients of the outcome equation in a sample selection model.
andrewscurv shows andrews curves for the principal components of the selected variables. The number of gridpoints can be chosen be the user and one or more group variables (disctrete type) can be selected.
andrewsrech performs a pca on the selected variables and creates a composed object of the andrews curves of the principal . components
ann is a tool to run a feed-forward neural network
annarchtest This macro calculates either the Lagrange Multiplier (LM) form or the T-Rsquare (TR2) form of a test for conditional heteroskedasticity based on Artificial Neural Networks. The first argument of the function is the vector of residuals, the second optional argument is the order of the test, the third optional argument is the number of hidden units of the Neural Network. The second optional argument is either a vector or a scalar. If no second argument is provided, the default orders are 2, 3, 4, and 5. The third argument may be either a vector, or a scalar. If both second and third arguments are vectors, the test will be calculated for all combinations of orders and hidden units. If no third argument is provided, the number of hidden units by default is set to 3. The fourth argument is the form of the test. This argument is a string of characters, which can be either "LM" or "TR2". The default fourth argument is "LM", i.e., the Lagrange Multiplier form. The macro returns in the first column the order of the test, in the second column the number of hidden units, in the third column the value of the test, in the fourth column the 95% critical value of the null hypothesis for that order, and in the fifth column the P-value of the test.
annlintest This macro calculates the neural network test for neglected nonlinearity proposed by Lee, White and Granger (1993). This statistic is evaluated from uncentered squared multiple correlation of an auxiliary regression in which we regress the residuals of a linear regression on the regressors of this regression and the principal components of a nonlinear transformation of the regressors. The first argument of the macro is the series y. The second argument is either a set of regressors X if the series is regressed on X, or the number of lags if the series is regressed on its lagged realizations. The macro adds automatically a constant if the constant term is missing in X. If the series is regressed on its past realizations, then the second argument, i.e., the number of lags, may be a vector. In that case, the corresponding linear models and statistics for neglected nonlinearity are computed. The third optional argument is the number of hidden units of the neural network, which should be greater than or equal to 3. The fourth optional argument is the number of principal components used in the auxiliary regression. The number of principal components should be less than the number of corresponding hidden units. The default third argument is the vector (10,20), the default fourth argument is the vector (2,3). If the series is regressed on a set of exogeneous variables X, the macro returns the number of principal components used in the auxiliary regression, the value of the test, the 95% critical value for the null hypothesis of the test, and the P value of the test. If the series is regressed on its past realizations, the number of lagged explanatory variables is also displayed.
aorBgen auxiliary quantlet for full VAR model analysis
append Appends an object to the specified list. If the appended object is temporary, the component gets the name el<position>. If the first argument is not a list, it will be changed to a list with itself as first component.
arbitrage calculates an arbitrage table considering put and calls with the same strike price
archest estimates a GARCH process with mean zero by QMLE
archtest This macro calculates either the Lagrange Multiplier (LM) form or the R squared (TR2) form of Engle's ARCH test. The first argument of the function is the vector of residuals, the second optional argument is the lag order of the test. This ; second argument may be either a scalar, or a vector. In the later case, the test is evaluated for all the order components of the vector. If this second optional argument is not provided, the default lag orders are 2, 3, 4, and 5. The third optional argument is the form of the test. This argument is a string, which can be either "LM" or "TR2". The default third argument is "LM", i,e., the LM form. The macro returns in the first column the order of the test, in the second column the value of the test, in the third column the 95% critical value of the null hypothesis for that order, and in the fourth column the P-value of the test.
arcsin performs a arcus sinus transformation of the selected variables in ISTA. The transformed variables can replace the original ones or can be appended on the end of data.x. the type is automatically set continuous.
armacls estimates an autoregressive moving average process with mean zero by conditional least squares
armalik estimates an ARMA(1,1) process with mean zero by maximum likelihood using the innovation algorithm
arofva auxiliary quantlet for full VAR model analysis
aseq Computes an additive sequence.
asin Returns the arcsine of the elements of an array.
asinh Returns the inverse hyperbolic sine of the elements of an array.
asset program to calculate option prices
atan Returns the arctangent in radian of the elements of an array.
atan2 Computes elementwise the angle in radian between the positive part of the x-axis and the line with origin in (0,0) which contains the point (x, y).

atanh Returns the inverse hyperbolic tangent of the elements of an array.
atof Converts strings to numbers.

axesoff All plots created afterwards have invisible axes.

axeson All plots created afterwards have visible axes.


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, 21.9.2000