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]  0.004195649 -0.022878205  0.052008113
#> 
#> [[2]]
#> [1]  0.01108836 -0.02994697  0.01811022
#> 
#> [[3]]
#> [1]  0.005058385 -0.048432858  0.025792010
#> 
#> [[4]]
#> [1]  0.01735349 -0.03685342  0.01468496
#> 
#> [[5]]
#> [1] 0.01274581 0.01093565 0.02903878
#> 
#> [[6]]
#> [1] -0.004008343  0.025064182  0.063727909
#> 
#> [[7]]
#> [1]  0.010631861  0.007198799 -0.033914896
#> 
#> [[8]]
#> [1] -0.034511046  0.001020017  0.008503482
#> 
#> [[9]]
#> [1] -0.080797255  0.012859861 -0.007423875
#> 
#> [[10]]
#> [1] -0.02193760 -0.00686005 -0.01838142
#>