| addfnci | auxiliary quantlet for cointegration |
| agen | auxiliary quantlet for VAR models |
| aorBgen | auxiliary quantlet for full VAR model analysis |
| arofva | auxiliary quantlet for full VAR model analysis |
| bgen | auxiliary quantlet for full VAR model analysis |
| cfc1diff | Forecasting undifferenced time series in VAR models |
| chol | computes the Cholesky decomposition of a symmetric, positive definite matrix |
| ciirboot | 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 the Bootstrap, 1993). |
| coeffba | auxiliary quantlet for full VAR model analysis |
| coeffest | estimates the coefficients of a full VAR model |
| coeffss | estimates parameters of Subset VAR |
| covabc | Covariance matrix of C=A*B, Reduced Rank VAR Model |
| covabrr | covariance matrix A*B, reduced rank VAR model |
| covarr | covariance matrix A, reduced rank VAR model |
| covbrr | Covariance matrix B, reduced rank VAR Model |
| covcheck | checks if the covariance matrix is singular |
| covfore2 | Computes forecast MSE matrix for undiff. time series |
| covforec | calculates the forecast MSE matrix for VAR models |
| covmlrr | covariance matrix used for reduced rank models |
| covmwgen | generates covariance matrix of the mean in VAR |
| covres | auxiliary quantlet for full VAR models |
| criterss | calculates selection criteria for Subset VAR |
| dgenci | auxiliary quantlet for cointegration |
| diagrv | replaces the diagonal of x by v |
| domulti | domulti is the starting quantlet for the library multi. The user can interactively transform the data, do preliminary analysis, select the model type, etc. |
| estabr | estimation of reduced rank VAR model |
| evci | auxiliary quantlet for cointegration |
| eye | creating a d-dimensional identity matrix |
| fgenci | auxiliary quantlet for cointegration |
| floatinf | provides information about real numbers within the interval [.5,0) in the form of x=a*10^b, b is bounded by -20 |
| fncovci | auxiliary quantlet for cointegration |
| fnrici | auxiliary quantlet for cointegration |
| fnyzci | auxiliary quantlet for cointegration |
| fnzzci | auxiliary quantlet for cointegration |
| forec2 | Forecasting in VAR Models with undifferencing |
| forecast | Forecasting in VAR Models |
| gammaci | auxiliary quantlet for cointegration |
| hgen | auxiliary quantlet for full VAR model analysis |
| hgenrr | Generation of H for the Reduced Rank VAR Model |
| 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.
|
| 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(). |
| itediff | calculates the i^th difference of a time series |
| ivforec | Computes forecast intervals for VAR Models |
| jagen | auxiliary quantlet for VAR models |
| jbgen | auxiliary quantlet for full VAR model analysis |
| jotaAorB | auxiliary quantlet for VAR models |
| kommumat | generates a help matrix for Subset VAR models |
| lgenci | auxiliary quantlet for cointegration |
| modelci | general analysis for cointegration |
| modelfr | general analysis for the Full VAR Model, called by the quantlet domulti |
| modelrr | general analysis for the Reduced Rank VAR Model, called by the quantlet domulti |
| modelss | general analysis for the Subset VAR Model, called by the quantlet domulti |
| multimain | sets defaults for quantlib multi |
| multiplot | Plots K-dimensional time series. |
| multitest | executes some tests for the quantlets defined in multi.lib. Is invoked by vertestl(). |
| normalt | multivariate normality tests |
| omegagen | calculates the correction term for MSE matrix of h-step forecasts in VAR models |
| omerrgen | Generation of Omega for the reduced rank VAR model |
| omgenci | auxiliary quantlet for cointegration |
| ones | creating a n x d dimensional matrix of ones |
| phigen | auxiliary quantlet for full VAR model analysis |
| portmant | calculates the multivariate portmanteau statistic |
| power | calculates x to the power of exponent |
| prognos2 | Forecasts of undifferenced series for VAR Models |
| prognose | forecasting in VAR models |
| residuen | calculates residuals for VAR models |
| rev | reverts the order of the rows of the input matrix |
| rgenss | generates the restriction matrix for Subset VAR |
| rici | auxiliary quantlet for cointegration |
| rootsci | calculates characteristic roots of VAR operator |
| selec | selects rows from the matrix mat |
| sfcoeff | estimates standard errors of parameter estimates |
| sfvonbss | standard errors of parameters for Subset VAR |
| sfvonmw | standard errors for mean in VAR models |
| shiftr | Shifts the rows of a matrix |
| sigma1 | auxiliary quantlet for full VAR model analysis |
| sijci | auxiliary quantlet for cointegration |
| simvar | computes a multidimensional autoregressive time series. |
| spur | computes the trace of the matrix |
| station | test for structural change (for VAR models) |
| strucbru | auxiliary quantlet for multi |
| varml |
computes the maximum likelihood estimates of the
model parameters (beta) and covariance (s) of residuals
of a VAR(p) model without intercept
|
| varorder | standard selection criteria for Full VAR models |
| varunls | computes the unconstrained least squares estimates of the model parameters (B), residuals (u), variance-covariance matrix of the residuals (s), and autocovariance matrix of the time series (g) of a K-dimensional VAR(p) model with/ without intercept |
| ymulz | auxiliary matrix multiplication for least squares regression |
| yzci | auxiliary quantlet for cointegration |
| zgenci | auxiliary quantlet for cointegration |
| zmulz | auxiliary matrix multiplication for least squares regression |
| zxgen | concatenates a VAR series |
| zzgenci | auxiliary quantlet for cointegration |