View source: R/SimulatedDataGenerator.r
SimulatedDataGenerator | R Documentation |
This function is used to generate simulated data for simulation studies with ARMA and MCD correlation structures.
SimulatedDataGenerator( Num.of.Obs, Num.of.TimePoints, Fixed.Effs, Random.Effs, Cor.in.DesignMat, Missing, Cor.Str, HSD.DesignMat.para, ARMA.para )
Num.of.Obs |
the number of subjects will be simulated. |
Num.of.TimePoints |
the maximum number of time points among all subjects. |
Fixed.Effs |
a vector of regression coefficients. |
Random.Effs |
a list of covariance matrix and the degree of freedom, |
Cor.in.DesignMat |
the correlation of covariates in the design matrix. |
Missing |
a list of the missing mechanism of observations, 0: data is complete, 1: missing complete at random, 2: missing at random related to responses , and 3: 2: missing at random related to covariates and the corresponding regression coefficients (weights) on the previous observed values either responses or covariates, e.g., |
Cor.Str |
the model for correlation structure, |
HSD.DesignMat.para |
if |
ARMA.para |
if |
a list containing the following components:
The simulated response variables y, covariates x's, and subject identifcation id.
The given values of fixed effects .
The given values of parameters in ARMA model.
The given values of parameters in ARMA model.
## Not run: library(BayesRGMM) rm(list=ls(all=TRUE)) Fixed.Effs = c(-0.2, -0.3, 0.8, -0.4) P = length(Fixed.Effs) q = 1 #number of random effects T = 5 #time points N = 100 #number of subjects num.of.iter = 100 #number of iterations HSD.para = c(-0.5, -0.3) #the parameters in HSD model a = length(HSD.para) w = array(runif(T*T*a), c(T, T, a)) #design matrix in HSD model for(time.diff in 1:a) w[, , time.diff] = 1*(as.matrix(dist(1:T, 1:T, method="manhattan")) ==time.diff) #Generate a data with HSD model HSD.sim.data = SimulatedDataGenerator(Num.of.Obs = N, Num.of.TimePoints = T, Fixed.Effs = Fixed.Effs, Random.Effs = list(Sigma = 0.5*diag(1), df=3), Cor.in.DesignMat = 0., Missing = list(Missing.Mechanism = 2, RegCoefs = c(-1.5, 1.2)), Cor.Str = "HSD", HSD.DesignMat.para = list(HSD.para = HSD.para, DesignMat = w)) #the proportion of 1's ones = sum(HSD.sim.data$sim.data$y==1, na.rm=T) num.of.obs = sum(!is.na(HSD.sim.data$sim.data$y)) print(ones/num.of.obs) #the missing rate in the simulated data print(sum(is.na(HSD.sim.data$sim.data$y))) #===========================================================================# #Generate a data with ARMA model ARMA.sim.data = SimulatedDataGenerator(Num.of.Obs = N, Num.of.TimePoints = T, Fixed.Effs = Fixed.Effs, Random.Effs = list(Sigma = 0.5*diag(1), df=3), Cor.in.DesignMat = 0., list(Missing.Mechanism = 2, RegCoefs = c(-1.5, 1.2)), Cor.Str = "ARMA", ARMA.para=list(AR.para = 0.8)) ## End(Not run)
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