sims.R

sims <- list(
  # 1. intercept only, but increasing variance
  list(seed=11001, n=200,  err=function(x) {rnorm(length(x), 0, 0.1+x)},
       errvar=1, mod=y~X1, coefs=c(3,0),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1))),
  # 2. SLR, constant variance
  list(seed=11001, n=200,  err=function(x) {rnorm(length(x), 0, 0.3)},
       errvar=0, mod=y~X1, coefs=c(5,-1),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1))),
  # 3. SLR, increasing variance
  list(seed=11001, n=200,  err=function(x) {rnorm(length(x), 0, 0.1+x)},
       errvar=1, mod=y~X1, coefs=c(5,-1),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1))),
  # 4. multiple variables, constant variance
  list(seed=11001, n=200,  err=function(x) {rnorm(length(x), 0, 0.1)},
       errvar=0, mod=y~X1+X2+X3+X4+X5, coefs=c(1,-3,2,2,-1,-2),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1),c(0,1),c(0,1),c(0,1),c(0,1))),
  # 5. multiple variables, non-constant variance:
  list(seed=11001, n=200,  err=function(x) {rnorm(length(x), 0, 0.1+x)},
       errvar=1, mod=y~X1+X2+X3+X4+X5, coefs=c(1,-3,2,2,-1,-2), 
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1),c(0,1),c(0,1),c(0,1),c(0,1))),
  # 6. variance depends on x1, x2
  list(seed=11001, n=200,  err=function(x1, x2) {rnorm(length(x1), 0, 0.1+x1+1.3*x2)},
       errvar=c(1,2), mod=y~X1+X2+X3+X4+X5, coefs=c(1,-3,2,2,-1,-2), 
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1),c(0,1),c(0,1),c(0,1),c(0,1))),
  # 7. non-normal errors
  list(seed=11001, n=200,  err=function(x) {rlnorm(length(x), 0, 0.75)},
       errvar=0, mod=y~X1+X2+X3+X4+X5, coefs=c(1,-3,2,2,-1,-2),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1),c(0,1),c(0,1),c(0,1),c(0,1))),
  # 8. non-normal errors which depend on a variable
  list(seed=11001, n=200,  err=function(x) {rlnorm(length(x), 0, 0.25+0.5*x)},
       errvar=1, mod=y~X1, coefs=c(2, -2),
       qns=seq(0.1,0.9,by=0.1),
       B=0, reps=100, xrng=rbind(c(0,1)))
)