the estimates for the components of an additive (partial linear) model are calculated. If the local linear smoother is applied, the first derivatives are calculated as well, additionally the second derivatives if the local quadratic smoother is chosen.
auxiliary quantlet that provides the analytical derivatives of the Gaussian log-likelihood of a bivariate BEKK-type volatility model with respect to its parameters
estimates the BEKK (Baba, Engle, Kraft, Kroner) volatility representation for a bivariate conditionally heteroscedastic time series and evaluates the maximum of the quasi log likelihood function in a GARCH(1,1) frame of the following form: S_t=C_(0)^T*C_(0)+A_(11)^T*e_(t-1)*e_(t-1)^T*A_(11)+G_(11)
linear binning for univariate data, given the binwidth and optionally the origin of the bin grid. The smallest grid with width d that covers the data is found and the data are binned to this grid using the linear binning rule.
direct computation of the autocovariances of the bincounts needed for fast computation of the kernel estimates of the integrated squared density derivatives.
calculates the price for path dependent options in the Black Scholes model by applying Quasi-Monte Carlo simulation in connection with a Brownian Bridge construction.
calculates the option price and its standard deviation for path independent options in the multi-dimensional Black Scholes model by Monte Carlo simulation.
calculates the option price and its standard deviation for path independent options in the multi-dimensional Black Scholes model by Monte Carlo simulation.
computes price of the CAT bond paying only coupons for the given claim amount distribution and the non-homogeneous Poisson process governing the flow of losses
computes price of the zero-coupon CAT bond for the given claim amount distribution and the non-homogeneous Poisson process governing the flow of losses.
computes the autocorrelation function (acf) and the Box-Ljung statistics for autocorrelation in a time series. Additionally, the p-values for the statistic are computed.
computes the autocorrelation function (acf) and the Box-Pierce statistics for autocorrelation in a time series. Additionally, the p-values for the statistic are computed.