Auxiliary routine for rICfil Calibrates the robust IC's for a given State Space model to a given relative efficiency loss in terms of the MSE in the ideal model. 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 ~
Auxiliary routine for rLSfil Calibrates the robust LS- Filter for a given State Space model to a given relative efficiency loss in terms of the MSE in the ideal model. 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),
Inside a switch-endsw block case controls the execution of an alternative. If the condition of case is true, the following block is executed similar to an if-endif statement. The keyword break serves as end marker of case and leaves the switch block at the position of endsw. When break is omitted,
creates dummy variables from a data with respect to distinct realizations. The default reference category is the minimal value in each column. Alternatively, categorization can be done by giving a value or the index (rank among the realizations) in a column.
returns the values of the mixture of exponentials cummulative distributions function with parameters alpha, beta1 and beta2 for the elements of an array.
Cdfncb2 returns the values of the noncentral beta-distribution function with parameters a and b and the parameter of noncentrality l for the elements of an array.
Cdfncchi2 returns the values of the noncentral chi-square distribution function with d degrees of freedom and the parameter of noncentrality l for the elements of an array.
Cdfncf2 returns the values of the noncentral F-distribution function with d1 and d2 degrees of freedom and the parameter of noncentrality l for the elements of an array.
Generates specific functions (Jump, Up-down, Sine, Freq. sine and Doppler). If all entries of sel are zero then you can choose interactively the function otherwise the selected function will be generated.
Enforces a specific view of the wavelet mother coefficients (Standard, Ordered, Circle and Partial sum). If none is selected then the old view will be returned.
Computes two sided bootstrap confidence intervals for impulse responses for a K-dimensional VAR(p) by resampling the estimated residuals. The confidence intervals are computed using the methodology of Hall (The Bootstrap and the Edgeworth Expansion, 1992) and Efron & Tibshirani (An Introduction to
This quantlet computes a committee of networks with nets of the form single layer feedforward perceptron. The quantlet can be used alone or in connection with the library ISTA. The standalone version also needs the parameter data. Just choose 0 for the input. The number of nets to build the committ
This quantlet computes a committee of networks with nets of the form single layer feedforward perceptron. The quantlet can be used alone or in connection with the library ISTA. The standalone version also needs the parameter data. Just choose 0 for the input. The number of nets to build the committ
Checks whether an object has a specific component or not. If the first argument is a string, the object with the specified name is regarded as a list object.
computes a linkage table between the rows and columns of a contingency table by maximum value of correspondence. The number of correspondences is the minimum of number or dimensions of the contingency table.
transforms the values of the upper triangle of a correlation matrix into distances, and it stores these distances into a vector regarding the sequence described in agglom
Implements the Cornish-Fisher expansion for arbitrary orders. The algorithm is related, but not identical to, the algorithm "AS269" published in "Applied Statistics".
corresp executes Correspondence Analysis which analyses and describes a contingency table cross-tabulations) in terms of a reduced number of dimensions. Correspondence Analysis can be viewed as finding the best simultaneous representation of two sets that comprise the rows and columns of a data mat
Computes the correlation integral for time series. The instantaneous state of a dynamical system is characterized by a point in phase space. A sequence of such states subsequent in time defines the phase space trajectory. If the system is governed by deterministic laws, then after a while, it will
CPC computes the common eigenmatrix, eigenvalues, corresponding standard errors and estimated population covariance matrices from sample covariances of k groups using maximum likelihood
CPCFGalg implements the FG-Algorithm which finds a common orthogonal transformation matrix in order to simultaneously diagonalize several positive definite symmetric matrices.
CPCp computes the common eigenmatrix, eigenvalues, corresponding standard errors, and estimated population covariance matrices from sample covariances of k groups assuming q common eigenvectors in B; CPCp uses maximum likelihood
CPCprop computes the common eigenmatrix, eigenvalues, correlation coefficients, their standard errors and their estimated population covariance matrices from sample covariances of k groups under the restriction that eigenvalues among groups are linked by a positive constant. Estimation is done usin
creates a functional data basis in two steps: it recognizes the type of basis by use of several variant spelling and sets up the functional data basis depending on the type.
computes pairwise crosstables from all columns of a data matrix, gives the result of a Chi-square independence test and computes contingency coefficients.
csort sorts the rows of a complex matrix with respect to the absolute value of the complex numbers. If a column c is specified the rows of the matrix will be ordered with respect to the elements of column c in ascending (descending) order.
sorts with respect to either a real part of a column or an imaginary part of a column c. If 1 <= c <= cols(xr) it sorts after the real part of x, if cols(xr) < c <= cols(xr)+cols(xi) it sorts the imaginary part after column c-cols(xr).