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

## K

KA KB KC KD KE KF KG KH KI KJ KK KL KM KN KO KP KQ KR KS KT KU KV KW KX KY KZ
kalmanmain
sets defaults for library kalman
kalmantest
Tests the quantlets of the kalman library.
kaplanmeier
Calculation of the Kaplan-Meir (product limit) estimator of the hazard rate and the survivor function for a set of durations. The first column of the input is a censorship indicator variable, (equal to zero if the duration is censored, and to one otherwise); the second column is the duration.
kem
Calculates estimates of mu, F, Q and R in a state-space model using EM-algorithm. The state-space model is assumed to be in the following form: y_t = H x_t + v_t x_t = F x_t-1 + w_t x_0 ~ (mu,Sig), v_t ~ (0,Q), w_t ~ (0,R)
kemitor
Calculates observations of a given state-space model. The state-space model is assumed to be in the following form: y_t = H x_t + ErrY_t x_t = F x_t-1 + ErrX_t x_0 = mu
kemitor2
Simulates observations and states of a given state-space-model - just as kemitor by Petr Franek (quantlib times) - but this time also the states are returned. The state-space model is assumed to be in the following form: y_t = H x_t + ErrY_t x_t = F x_t-1 + ErrX_t x_0 =
kernelmain
generate the volume of the unit balls
kerneltest
kerneltest tests all the aforementioned quantlets of the kernel.lib
kfilter
Calculates a filtered time series (uni- or multivariate) using the Kalman filter equations. The state-space model is assumed to be in the following form: y_t = H x_t + v_t x_t = F x_t-1 + w_t x_0 ~ (mu,Sig), v_t ~ (0,Q), w_t ~ (0,R) All parameters are assumed to be known.
kfilter2
Calculates a filtered time serie (uni- or multivariate) using the Kalman filter equations. The state-space model is assumed to be in the following form: y_t = H x_t + v_t x_t = F x_t-1 + w_t x_0 ~ (mu,Sig), v_t ~ (0,Q), w_t ~ (0,R) All parameters are assumed known.
kmcont
performes a K-means cluster analysis of the rows of a contingency table including the multivariate graphic using the correspondence analysis; makes available the factorial coordinates (scores)
kmeans
performs cluster analysis, i.e. computes a partition of n row points into K clusters.
knn
computes a running mean over (2k+1) consecutive values of a given vector. To have the same length at the beginning and at the end the first and last value are repeated k times.
kommumat
generates a help matrix for Subset VAR models
kpss
Calculation of the KPSS statistics for I(0) against long-memory alternatives. We consider two tests, denoted by KPSS_mu and KPSS_t based on a regression on a constant mu, and on a constant and a time trend t, respectively. The quantlet returns the value of the estimated statistic for the two tests,
kpssnum
Calculates the KPSS statistics for I(0) processes against long-memory alternatives. We consider two tests, denoted by KPSS_mu and KPSS_t, based on a regression on a constant mu, and on a constant and a time trend t, respectively. The quantlet returns the value of the estimated statistic for two the
kron
Computes the Kronecker product of two matrices.
ksmoother
Calculates a smoothed time serie (uni- or multivariate) using the Kalman smoother equations. The state-space model is assumed to be in the following form: y_t = H x_t + v_t x_t = F x_t-1 + w_t x_0 ~ (mu,Sig), v_t ~ (0,Q), w_t ~ (0,R) All parameters are assumed known.
kstat
calculates Kolmogorov statistics
kurtosis
Computes the kurtosis for a given vector.

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