R/fitdistcens.R

#############################################################################
#   Copyright (c) 2009 Marie Laure Delignette-Muller                                                                                                  
#                                                                                                                                                                        
#   This program is free software; you can redistribute it and/or modify                                               
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#   (at your option) any later version.                                                                                                            
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#   GNU General Public License for more details.                                                                                    
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#############################################################################
### fit parametric distributions for censored data
###
###         R functions
### 

fitdistcens <- function (censdata, distr, start=NULL, fix.arg=NULL, 
                         keepdata = TRUE, keepdata.nb=100, ...) 
{
    if (missing(censdata) ||
        !(is.vector(censdata$left) & is.vector(censdata$right) & length(censdata[, 1])>1))
        stop("datacens must be a dataframe with two columns named left 
            and right and more than one line")
    leftsupright <- censdata$left>censdata$right
    leftsupright <- leftsupright[!is.na(leftsupright)]
    if (any(leftsupright))
        stop("each left value must be less or equal to the corresponding right value")
    if (!is.character(distr)) distname <- substring(as.character(match.call()$distr), 2)
    else distname <- distr
    ddistname <- paste("d", distname, sep="")
    if (!exists(ddistname, mode="function"))
        stop(paste("The ", ddistname, " function must be defined"))
    pdistname <- paste("p", distname, sep="")
    if (!exists(pdistname, mode="function"))
        stop(paste("The ", pdistname, " function must be defined"))
    if(!is.logical(keepdata) || !is.numeric(keepdata.nb) || keepdata.nb < 3)
      stop("wrong arguments 'keepdata' and 'keepdata.nb'.")
    
    #encapsulate three dots arguments
    my3dots <- list(...)    
    if (length(my3dots) == 0) 
      my3dots <- NULL
    
    #format data for calculation of starting values
    pseudodata <- cens2pseudo(censdata)$pseudo
    
    # manage starting/fixed values: may raise errors or return two named list
    arg_startfix <- manageparam(start.arg=start, fix.arg=fix.arg, obs=pseudodata, 
                                distname=distname)
    
    #check inconsistent parameters
    argddistname <- names(formals(ddistname))
    hasnodefaultval <- sapply(formals(ddistname), is.name)
    arg_startfix <- checkparamlist(arg_startfix$start.arg, arg_startfix$fix.arg, 
                                   argddistname, hasnodefaultval)
    #arg_startfix contains two names list (no longer NULL nor function)
    
    #store fix.arg.fun if supplied by the user
    if(is.function(fix.arg))
      fix.arg.fun <- fix.arg
    else
      fix.arg.fun <- NULL
    
    # check d, p, q, functions of distname
    dpq2test <- c("d", "p")
    resdpq <- testdpqfun(distname, dpq2test, start.arg=arg_startfix$start.arg, 
                         fix.arg=arg_startfix$fix.arg, discrete=FALSE)
    if(any(!resdpq$ok))
    {
      for(x in resdpq[!resdpq$ok, "txt"])
        warning(x)
    }
    
        
    # MLE fit with mledist 
    mle <- mledist(censdata, distname, start=arg_startfix$start.arg, 
                   fix.arg=arg_startfix$fix.arg, checkstartfix=TRUE, ...)
    if (mle$convergence>0) 
        stop("the function mle failed to estimate the parameters, 
        with the error code ", mle$convergence) 
    estimate <- mle$estimate
    
    if(!is.null(mle$hessian)){
        #check for NA values and invertible Hessian
        if(all(!is.na(mle$hessian)) && qr(mle$hessian)$rank == NCOL(mle$hessian)){
            varcovar <- solve(mle$hessian)
            sd <- sqrt(diag(varcovar))
            correl <- cov2cor(varcovar)
        }else{
            varcovar <- NA
            sd <- NA
            correl <- NA
        }
    }else{
        varcovar <- NA
        sd <- NA
        correl <- NA
    }
    
    loglik <- mle$loglik
    n <- nrow(censdata)
    npar <- length(estimate)
    aic <- -2*loglik+2*npar
    bic <- -2*loglik+log(n)*npar
         
    fix.arg <- mle$fix.arg
    weights <- mle$weights
    
    #needed for bootstrap
    if (!is.null(fix.arg)) 
      fix.arg <- as.list(fix.arg)
    
    if(keepdata)
    {
      reslist <- list(estimate = estimate, method="mle", sd = sd, cor = correl, 
                      vcov = varcovar, loglik = loglik, aic=aic, bic=bic, n=n, censdata=censdata, 
                      distname=distname, fix.arg=fix.arg, fix.arg.fun = fix.arg.fun, 
                      dots=my3dots, convergence=mle$convergence, discrete=FALSE,
                      weights = weights)
    }else
    {
      n2keep <- min(keepdata.nb, n)-4
      imin <- unique(apply(censdata, 2, which.min))
      imax <- unique(apply(censdata, 2, which.max))
      subdata <- censdata[sample((1:n)[-c(imin, imax)], size=n2keep, replace=FALSE), ]
      subdata <- rbind.data.frame(subdata, censdata[c(imin, imax), ])
      
      reslist <- list(estimate = estimate, method="mle", sd = sd, cor = correl, 
                      vcov = varcovar, loglik = loglik, aic=aic, bic=bic, n=n, censdata=subdata, 
                      distname=distname, fix.arg=fix.arg, fix.arg.fun = fix.arg.fun, 
                      dots=my3dots, convergence=mle$convergence, discrete=FALSE,
                      weights = weights)
    }
    
    return(structure(reslist, class = "fitdistcens"))
        
}

print.fitdistcens <- function(x, ...){
    if (!inherits(x, "fitdistcens"))
        stop("Use only with 'fitdistcens' objects")
    cat("Fitting of the distribution '", x$distname, "' on censored data by maximum likelihood \n")
    cat("Parameters:\n")
    print(cbind.data.frame("estimate" = x$estimate), ...)

    if(!is.null(x$fix.arg))
    {
      if(is.null(x$fix.arg.fun))
      {
        cat("Fixed parameters:\n")
      }else
      {
        cat("Fixed parameters (computed by a user-supplied function):\n")
      }
      print(cbind.data.frame("value" = unlist(x$fix.arg)), ...)
    }

}

plot.fitdistcens <- function(x, ...){
    if (!inherits(x, "fitdistcens"))
        stop("Use only with 'fitdistcens' objects")
    if(!is.null(x$weights))
      stop("The plot of the fit is not yet available when using weights")
  plotdistcens(censdata=x$censdata, distr=x$distname, 
    para=c(as.list(x$estimate), as.list(x$fix.arg)), ...)
    
}

summary.fitdistcens <- function(object, ...){
    if (!inherits(object, "fitdistcens"))
        stop("Use only with 'fitdistcens' objects")
    object$ddistname <- paste("d", object$distname, sep="")
    object$pdistname <- paste("p", object$distname, sep="")
    
    class(object) <- c("summary.fitdistcens", class(object))    
    object
}

print.summary.fitdistcens <- function(x, ...){
    if (!inherits(x, "summary.fitdistcens"))
        stop("Use only with 'fitdistcens' objects")
    ddistname <- x$ddistname
    pdistname <- x$pdistname
    
    cat("Fitting of the distribution '", x$distname, 
    "' By maximum likelihood on censored data \n")
    cat("Parameters\n")
    print(cbind.data.frame("estimate" = x$estimate, "Std. Error" = x$sd), ...)
    
    if(!is.null(x$fix.arg))
    {
      if(is.null(x$fix.arg.fun))
      {
        cat("Fixed parameters:\n")
      }else
      {
        cat("Fixed parameters (computed by a user-supplied function):\n")
      }
      print(cbind.data.frame("value" = unlist(x$fix.arg)), ...)
    }
    
    cat("Loglikelihood: ", x$loglik, "  ")
    cat("AIC: ", x$aic, "  ")
    cat("BIC: ", x$bic, "\n")
    if (length(x$estimate) > 1) {
        cat("Correlation matrix:\n")
        print(x$cor)
        cat("\n")
    }
    invisible(x)
}

#see quantiles.R for quantile.fitdistcens
#see logLik.R for loglik.fitdistcens
#see vcov.R for vcov.fitdistcens
#see coef.R for coef.fitdistcens

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fitdistrplus documentation built on May 2, 2019, 7:24 a.m.