# R/plot.pstp.R In presmTP: Methods for Transition Probabilities

#### Documented in plot.pstp

```#' Plot for an object of class "pstp"
#'
#' @description It draws the estimated probabilities.
#'
#' @param x A fitted pstp object as produced by presmTP.
#' @param state_ini Initial state of the transition. Defaults to state_ini=0
#' @param ... For future methods.

#' @return No value is returned.
#'
#' @examples
#' res<- presmTP(data = colonIDM, s = 365,method = "uns")
#' plot(res)
#'
#' @author Gustavo Soutinho, Luis Meira-Machado, Pedro Oliveira.

plot.pstp<- function(x=object,  state_ini=0, ...){

#object<-res

#x=object

###x<-res #para testar erro!! acrescentei

object <- x

if (inherits(object, "pstp")){

if (class(object)[1] %in% c("Unsmooth", "Nonparametric", "Logit", "Logit.gam", "Probit", "Cauchit")) {

if(state_ini==0){

times<-object\$est0\$t
s<-object\$s
p00<-object\$est0\$p00
p01<-object\$est0\$p01
p02<-object\$est0\$p02

x=list(times, cbind(p00, p01, p02))

matplot(x=x[[1]], y=x[[2]], type="l", col=1:3,
ylab = paste('pij(', s,',t)', sep=''),lwd = 1)

legend("topright", legend=c("00", "01", "02"), text.col=1:3, cex=1)

}else{

times<-object\$est1\$t
s<-object\$s
p11<-object\$est1\$p11
p12<-object\$est1\$p12

x=list(times, cbind(p11, p12))

matplot(x=x[[1]], y=x[[2]], type="l", col=1:2,
ylab = paste('pij(', s,',t)', sep=''),lwd = 1)

legend("topright", legend=c("11","12"), text.col=1:2, cex=1)

}

}else{ #nao ser um dos metodos de estimacao

stop("Possible methods are 'uns', 'np', logit, 'logit.gam', 'probit', 'cauchit'.")
}

}else{

stop("Argument x must be either pstp object.")

}

} #fim function

```

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presmTP documentation built on Nov. 1, 2019, 7:45 p.m.