K

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.