Man pages for nielsaka/zeitreihe
Simulate, Estimate, Select, and Forecast Multiple Time Series Processes

all_trueAre all elements TRUE?
asy_cov_mat_struc_coeffTitle
check_stabilityCheck the stability criterion of a VAR(p) model
check_startDo all names start with "it"?
chol_decompCholesky Decomposition
commutation_matrixTitle
companion_formatConvert a VAR(p) model to VAR(1) companion format
conc_log_lik_initInitialise the Concentrated Log-Likelihood
cov_var_processCompute the Covariance Matrix of a VAR(p) Process
create_arp_dataCreate data using an AR(1)
create_svar_dataCreate data using a structural VAR
create_varp_dataCreate data using a reduced-form VAR
dm_col_indexColumn indices of duplication matrix
dm_indexIndices of a duplication matrix
duplication_matrixDuplication Matrix 'D'
duplication_matrix_ginverseMoore-Penrose inverse of duplication matrix 'D'
expander_eExpand a Matrix
gradient_var_initGradient of VAR reduced-form log-likelihood
is_identifiedVerify whether an SVAR model is identified
lag_lengthRetrieve number of lags
log_lik_initCreate a function to compute the log-likelihood
MA_coeffsMoving Average Coefficients
mean_var_processCompute the mean of a VAR(p) process
mle_varMaximum likelihood estimation of a VAR(p)
obs_lengthRetrieve number of observations
ols_choleskyEstimate Contemporaneous Structural Effects
ols_mvMultivariate ordinary least squares for VARs
rank_conditionCalculate ranks for identification
selection_matrixSelection matrix for imposing linear restrictions
selector_JCreate Selection Matrix 'J'
sMA_CIHall's percentile interval bootstrap
sMA_coeffsstructural moving average coefficients
split_templSample Splitting
var_lengthRetrieve number of variables
vecVectorise a matrix
vechVectorise a symmetric matrix
Y2ZCreate a regressor matrix for a VAR(p) model
nielsaka/zeitreihe documentation built on Nov. 9, 2019, 5:54 p.m.