Simulate Set Point Vectors from the Multivariate Normal Distribution

This function simulates random set point vectors from the multivariate normal distribution.

Usage

SimMuN(n, mu, vcov_mu_l)

Arguments

n

Positive integer. Number of replications.

mu

Numeric vector. Set point (\(\boldsymbol{\mu}\)).

vcov_mu_l

Numeric matrix. Cholesky factorization (t(chol(vcov_mu))) of the sampling variance-covariance matrix of \(\boldsymbol{\mu}\).

Value

Returns a list of random set point vectors.

See also

Other Simulation of State Space Models Data Functions: LinSDE2SSM(), LinSDECovEta(), LinSDECovY(), LinSDEInterceptEta(), LinSDEInterceptY(), LinSDEMeanEta(), LinSDEMeanY(), ProjectToHurwitz(), ProjectToStability(), SSMCovEta(), SSMCovY(), SSMInterceptEta(), SSMInterceptY(), SSMMeanEta(), SSMMeanY(), SimAlphaN(), SimBetaN(), SimBetaN2(), SimBetaNCovariate(), SimCovDiagN(), SimCovN(), SimIotaN(), SimMVN(), SimNuN(), SimPhiN(), SimPhiN2(), SimPhiNCovariate(), SimSSMFixed(), SimSSMIVary(), SimSSMLinGrowth(), SimSSMLinGrowthIVary(), SimSSMLinSDEFixed(), SimSSMLinSDEIVary(), SimSSMOUFixed(), SimSSMOUIVary(), SimSSMVARFixed(), SimSSMVARIVary(), SpectralRadius(), TestPhi(), TestPhiHurwitz(), TestStability(), TestStationarity()

Author

Ivan Jacob Agaloos Pesigan

Examples

n <- 10
mu <- c(0, 0, 0)
vcov_mu_l <- t(chol(0.001 * diag(3)))
SimMuN(n = n, mu = mu, vcov_mu_l = vcov_mu_l)
#> [[1]]
#> [1] -0.007423875 -0.047067673 -0.021937595
#> 
#> [[2]]
#> [1] -0.018381415  0.011810344  0.009970126
#> 
#> [[3]]
#> [1] -0.06159578  0.07372126 -0.04655702
#> 
#> [[4]]
#> [1] -0.003808598  0.031145857  0.011251237
#> 
#> [[5]]
#> [1] -0.03271647  0.03096005 -0.01941195
#> 
#> [[6]]
#> [1]  0.005917232 -0.012723710  0.025256800
#> 
#> [[7]]
#> [1]  0.022433221 -0.003152393 -0.068300011
#> 
#> [[8]]
#> [1] -0.01362470  0.02341088 -0.01656331
#> 
#> [[9]]
#> [1] -0.02290375 -0.04210809  0.03715096
#> 
#> [[10]]
#> [1] -0.084260999  0.047630028 -0.001905866
#>