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#' @title Generate binary data with 1-dependent correlated structure
#' @description
#' Equivalent to cBern(n, p, rho, type="1-dependent")
#'
#' @param n number of observations
#' @param p the vector of marginal probabilities with dimension m
#' @param rho either a non-negative value indecating the shared correlation coefficient
#' or and m-1 vector indicating the correlation coefficients between adjacent
#' variables.
#'
#' @return an n*p matrix of binary data
#' @examples
#' X <- cBern1dep(5, c(0.4,0.5,0.6), c(0.2,0.3))
#' @export
#'
cBern1dep <- function(n, p, rho){
m <- length(p)
if((length(rho)!=1)&(length(rho)!=(m-1))){
warning("Invalid Input: The length of rho has to be 1 or m-1.\n")
return(NaN)
}
res <- cBernMdep0(n,p,rho)
if(!is.na(res[1])){
message("Worked out!")
return (res)
}
else{
message("Now trying UYY method (Method 1).")
res <- cBernMdep1(n,p,rho)
if(!is.na(res[1])){
message("Worked out!")
return(res)
}
else{
warning("Invalid Input: Please adjust the setting of rho according to the instructions.")
}
}
}
# a <- cBernMdep(1,c(0.3,0.5,0.7,0.6),rep(0.328,3))
# hhwarnings()
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