R/SimHMM.R

In zoevanhavre/ZmixHMM: What the package does (one line)

 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimHMM<-function(Q,Mu, q0=NA, n=100){
        k<-dim(Q)[1]
        #stationary dist q0 for this:
      if( sum(is.na(q0)=="TRUE")<k ){ q0<-getq0(Q)}
        #state chain & ys
        X<-c(rep(0,n))
        Y<-c(rep(0,n))
        X[1]<-sample(c(1:k), size=1,prob =q0)

        for (i in 2:n){
        #states
        X[i]<-sample(c(1:k), size=1,prob =Q[X[i-1],]) }

                                #y's
                        #  for (i in 1:n){          Y[i]<-rnorm(1, Mu[X[i]], 1)}
         Y<-sapply( X, function(x)   rnorm(1, Mu[x], 1) )

        return(data.frame("States"=X, "Observed"=Y))
        }

 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))



#FunkSim1<-function(n){  data.frame( "States"=1, "Observed"=rnorm(n, mean=3, sd=1)) }

 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))


FunkSim1<-function(n){   SimHMM( Q=matrix( c(  0.2,0.3,0.5,    0.5,0.25,0.25,    0.25, 0.65, 0.1), nrow=3, byrow=T),  Mu= c(1,3,6),q0=NA, n)  }


 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimDensity1<-  function(x) { return(density_f2(  x$O, .Q= c(  0.2,0.3,0.5,   0.5,0.25,0.25,    0.25, 0.65, 0.1), .mu=c(1,3, 6), .q0=ALTERNATEq0(matrix(  c(.2,0.3,0.5,    0.5,0.25,0.25,    0.25, 0.65, 0.1), nrow=3, byrow=T)) ) )}

 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))



FunkSim2<-function(n){   SimHMM( Q=matrix( c(  0.8,0.1,0.1,    0.2,0.75,0.05,    0.1, 0.3, 0.6), nrow=3, byrow=T),  Mu= c(1,3,6),q0=NA, n)  }

#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimDensity2<-  function(x) { return(density_f2(  x$O, .Q= c( 0.8,0.1,0.1,    0.2,0.75,0.05,    0.1, 0.3, 0.6), .mu=c(1,3, 6), .q0=ALTERNATEq0(matrix(  c(0.8,0.1,0.1,    0.2,0.75,0.05,    0.1, 0.3, 0.6), nrow=3, byrow=T)) ) )}

#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))


FunkSim3<-function(n){
q1<-matrix(0.1, ncol=5, nrow=5)
diag(q1)<-.6
SimHMM( Q=q1,  Mu= c(-10, -5, 0, 5, 10),q0=NA, n)  }

#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimDensity3<-  function(x) {
  q1<-matrix(0.1, ncol=5, nrow=5)
diag(q1)<-.6
  return(density_f2(  x$O, .Q= c(q1), .mu=c(-10, -5, 0, 5, 10), .q0=ALTERNATEq0(q1)))}

#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

FunkSim4<-function(n){ q1<-matrix(0.1, ncol=5, nrow=5) ; diag(q1)<-.6 ; q1[5,]<-c(    .225,.225,.225, .225, 0.1) ;   SimHMM( Q=q1,  Mu= c(-1, 3,  5, 8, 20),q0=NA, n)  }



#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimDensity4<-  function(x) {  q1<-matrix(0.1, ncol=5, nrow=5) ; diag(q1)<-.6 ;q1[5,]<-c(    .225,.225,.225, .225, 0.1) ;  return(density_f2(  x$O, .Q= c(q1), .mu= c(-1, 3,  5, 8, 20), .q0=ALTERNATEq0(q1)))}



#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

FunkSimSEQ<-function(n){
        nrep<-n/100
        X_100<-c( rep(1, 20), rep(2, 15), rep(1, 5), rep(3, 3), rep( 1, 25), rep(2, 10), rep(1, 20), rep(3, 2))
         X<-rep(X_100, nrep)
         Y<-sapply( X, function(x)   rnorm(1, c(1,4,-10)[x], 1) )

       return(data.frame("States"=X, "Observed"=Y))
        }

#' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))


FunkSim0<-function(n){   SimHMM( Q=matrix( c(0.6,0.4,    0.7,0.3), nrow=2, byrow=T),  Mu= c(-1,2),q0=NA, n)  }


 #' Function to compute stationary distribution of HMM
#'
#' density of dirichlet
#' @param x, alpha, log=False
#' @keywords dirichlet
#' @export
#' @examples dDirichlet(c(.1, .9), c(0.1,0.1))

SimDensity0<-  function(x) { return(density_f2(  x$O, .Q= c(0.6,0.4,    0.7,0.3), .mu=c(-1,2), .q0=ALTERNATEq0(matrix( c(0.6,0.4,    0.7,0.3), nrow=2, byrow=T)) ) )}