TABLE OF CONTENTS

curveUpdate/evalparametric [ Functions ]

NAME

    evalparametric --- evaluate the parametric component of a curve

FUNCTION

Evaluate the parametric component of a curve, either at all observations or at a single observation.

SYNOPSIS

1923 evalparametric <- function(curve, i = 0)

INPUTS

    curve      an RCurve structure
    i          the index of the observation that should be evaluated (0=all)

OUTPUTS

    curve      the input curve, with x[i] reevaluated at curve$param.par

SOURCE

1926 {
1927     if(!curve$haspar) return(curve)
1928     if(i == 0) ind <- 1:length(curve$x) else ind <- i
1929     name <- curve$name
1930     dist <- curve$param.dist
1931     if(dist == "none") return(curve)
1932     # extract parameters and values at which to evaluate
1933     par <- curve$param.par
1934     x <- curve$x[ind]
1935     if(name == "hazard"){
1936         if(dist == "exponential"){
1937             # exponential components are parametrized by their log-baseline
1938             lambda <- exp(par)
1939             y <- rep(lambda, length(x))
1940             ycum <- x * lambda
1941         }
1942         if(dist == "weibull"){
1943             # weibull components are parametrized by their log-baseline and log-scale
1944             lambda <- exp(par[1])
1945             alpha <- exp(par[2])
1946              y <- alpha * lambda * x^(alpha - 1)
1947              ycum <- lambda * x^alpha
1948         }
1949         if(dist == "lognormal")
1950             stop("lognormal distribution currently not fully supported")
1951     }
1952     if(name == "frailty"){
1953         ycum <- NULL
1954         if(dist == "gamma"){
1955             # gamma components are parametrized by minus their log-shape
1956             alpha <- exp(-par)
1957             y <- dgamma(x, shape = alpha, rate = alpha)
1958         }
1959         if(dist == "lognormal"){
1960             # lognormal components are parametrized by their log-variance
1961             alpha <- exp(par)
1962             y <- exp(-(log(x) + alpha / 2)^2 / (2 * alpha)) / (x * sqrt(2 * pi * alpha))
1963         }
1964     }
1965     curve$param.y[ind] <- y 
1966     curve$param.ycum[ind] <- ycum
1967     if(curve$hasspline) {
1968          # reweight the curve if it has a spline component
1969          curve <- weightcurve(curve, i)
1970     }else{
1971         curve$y[ind] <- curve$param.y[ind]
1972         curve$ycum[ind] <- curve$param.ycum[ind]
1973     }  
1974     return(curve)
1975 }