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

ICerz - indexnaturalhermite - intest2d - isInf - istastatistic - ivforec
ICerz Auxiliary routine for rICfil:

- if possible - generates for Scores Lambda~N(0,FI) (FI:: Fisher-Info) a Hampel-Krasker-IC psi to efficiency loss e, i.e.

E psi Lambda' = unit(p) E psi=0 (1)

E |psi|^2= (1+e) tr (FI^{-1}) (2)

and psi= A Lambda w_b

w_b=min(1,b/|A Lambda|)

for dim p==1 a Newton-Algo is used for both a and b, for dim p>=2 for A a fixed-point-algorithm and for b a "careful" bisection method is used. Integration for A and p==2 is done by a Romberg-procedure. Integration for A and p>2 is done by a MC-procedure.

ICerzsep Auxiliary routine for rICfil:

- if possible - generates for Lambda=Lambda1+Lambda2, Lambda1~N(0,S1), Lambda2~N(0,S2) indep a Hampel-Krasker-IC psi to efficiency loss e, i.e.

E psi Lambda' = EM, E psi=0 (1)

E |psi|^2= (1+e) tr ((S1+S2)^{-1})

and psi= A (Lambda1 w_b + Lambda2)

w_b=min(1,b/|A Lambda1|)

For dim p==1 a Newton-Algo is used for both a and b, for dim p>=2 for A a fixed-point-algorithm and for b a "careful" bisection method is used. Integration for A and p==2 is done by a Romberg-procedure. Integration for A and p>2 is done by a MC-procedure.

if if does conditional branching, if the first element of the argument is true. If has to be followed by an endif. Else is an optional part of if sequences.

impres Computes the forecast error impulse responses of a K-dimensional VAR(p)-model from the model parameters 'a' up to 't' time periods after the shock.

index index generates a new matrix z from an old matrix x by resampling the rows of x depending on the index vector i.

indexcat returns the indices of the elements of a vector which fall into specified category.
indexentropy computes the Entropy index via kernel density estimation
indexfriedmantukey computes the Friedman Tukey index via kernel density estimation
indexhermite computes the Hermite index via kernel density estimation
indexlegendre computes the Legendre index via kernel density estimation
indexnaturalhermite computes the Natural Hermite index via kernel density estimation
influence displays the influence of price determining parameters on options. It is using the Black and Scholes formula.
init Supporting Quantlet for cartsplit
insert inserts an object to the specified position within a list.
interact interact estimates a model with interaction terms. It is using the marginal integration estimator with a local polynomial smoother. For details see Sperlich, Tjostheim, Yang (1997)
intertest1 intertest1 is testing for interaction of x_1 and x_2 in an additive regression model. It is looking at the interation estimate and using wild bootstrap. For details see Sperlich, Tjostheim, Yang (1997)
intertest2 intertest2 is testing for interaction of x_1 and x_2 in an additive regression model. It is looking at the estimate of the mixed derivative of the joint influence and using wild bootstrap. For details see Sperlich, Tjostheim, Yang (1997)
interval transforms the selected variables in a user specified interval. The transformed variables can replace the original ones or can be appended on the end of data.x. the type is automatically set continuous.
intest estimation of the univariate additive functions in a separable additive model using Nad.Watson, local linear or local quadratic
intest1 estimation of the univariate additive functions in a separable additive model using Nad.Wat.
intest2d estimation of a bivariate joint influence function and its derivatives in a model with possible interaction. When loc.lin.smoother is chosen you get the function estimate and the first derivatives in the first and second direction, when loc.quadr.smoother is chosen you get the function and the mixed derivative estimate.
intestpl estimation of the univariate additive functions in a separable additive partial linear model using local polynomial estimation
inv inv computes the inversematrix. As usally this functionality extends to higher dimensional arrays.

invdwt invdwt computes the inverse Discrete Wavelet Transformation of a vector.
invfft invfft computes the Inverse Fast Fourier Transformation of a complex vector.
invfwt invfwt computes the Fast Wavelet Transformation of a vector.
invfwt2 The algorithm invfwt2 is designed for 2 dimensional inverse wavelet transformation. The wavelet coefficients are stored in the matrix c.
invfwtin fwtin computes the inverse Fast Wavelet Transformation of all circular shifts from ti.
invv
ira Generation of menu system for impulse response analysis. When calling this quantlet a system of menus will appear on the screen that guides you through the stages of impulse response analysis for vector autoregressive models.

This quantlet defines the following pop-up menus: irairmax, iracoverage, irabootci, irayscale, iraimpulse, iraresponse, iraselectgraph, iramain, iradisplay, irainfodisplay.

This quantlet defines the following auxiliary functions: vector2string, strvector2string, comparevector.

The quantlet ira() communicates by one list ('m.*') with the pop-ups. The succesion of the pop-ups is controlled with two other lists ('enter.*' and 'return.*'). All lists are defined in ira().

isInf Determines whether elements of an array are infinity or -infinity (Inf or -Inf).
isNaN Determines whether elements of an array are missing values (NaN).
isNumber Determines whether elements of an array are usual figures or not (NaN, Inf, -Inf).
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=1,...,n

istaanova show the ANOVA table after performing a linear regression with Enter method for variable inclusion
istadata starts menu data in ISTA
istagraphic starts menu graphic in ISTA
istalinreg istalinreg computes the Least Squares estimate for the coefficients of a linear model with intercept in ISTA after chosing the Enter option. The estimate is given by b = INV(TRN(x) INV(om) x) TRN(x) INV(om) y.

istamain sets global display number equal to 0 and and loads the necessary libraries
istaprint creates menu button to print display
istastatistic starts menu statistic in ISTA
istatransformation starts menu transformation in ISTA
itediff calculates the i^th difference of a time series
itera Auxiliary routine for rICfil:

- if possible - solves for Lambda~N(0,FI) (FI:: Fisher-Info)

A^{-1} =E [ Lambda Lambda' w_b ] (1)

w_b=min(1,b/|A Lambda|)

using a fixed-point-algorithm

iteras Auxiliary routine for rICfil:

- if possible - solves for Lambda1~N(0,S1),Lambda2~N(0,S2) indep.

A^{-1} =E [ Lambda1 Lambda1' w_b ] + E [ Lambda2 Lambda2' ] (1)

w_b=min(1,b/|A Lambda1|)

using a fixed-point-algorithm

ivforec Computes forecast intervals for VAR Models

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