Hello there, I am currently perform a simulation on an AR(1) model with variable changes to sample size and population parameter (denoted as ?). For example, assume that we are simulating an AR(1) model with sample size ? {10,100} and ??{0.1,0.9} and repeat it 100 times. This can be done with the help of a looping function (crudely made) below. library(readr) library(MASS) library(dynlm) set.seed(2000) reps=100 nv <- c(10,100) phi.hat<- matrix(nrow=reps, ncol=length(nv)) #Looping 100 repeated samples @phi=0.9 for (i in 1:length(nv)){ n=nv[i] for (j in 1:reps){ Yi=V=ts(rnorm(n, mean=0, sd=1),start=1, end=n, frequency=1) Y=0+0.9*Yi[-1]+V eq1=dynlm(Y~L(Y,1)) phi.hat[j,i]=eq1$coefficients[2] } } #Looping 100 repeated samples @ phi=0.1 for (i in 1:length(nv)){ n=nv[i] for (j in 1:reps){ Yi=V=ts(rnorm(n, mean=0, sd=1),start=1, end=n, frequency=1) Y=0+0.1*Yi[-1]+V eq1=dynlm(Y~L(Y,1)) phi.hat[j,i]=eq1$coefficients[2] } } Having done this, I have received a relatively similar sample coefficient to population parameter (i.e., mean( phi_hat) ? phi). However, for phi=0.9, the value for mean(phi_hat) is not close to phi. I was wondering why this is the case. Thank you for reading this! Regards, Yanith [[alternative HTML version deleted]]