R: Distributions available in survreg.

dsurvreg {survival} | R Documentation

## Distributions available in survreg.

### Description

Density, cumulative distribution function, quantile function and random generation for the set of distributions supported by the `survreg` function.

### Usage

    dsurvreg(x, mean, scale=1, distribution='weibull', parms)
    psurvreg(q, mean, scale=1, distribution='weibull', parms)
    qsurvreg(p, mean, scale=1, distribution='weibull', parms)
    rsurvreg(n, mean, scale=1, distribution='weibull', parms)

### Arguments

`x` | vector of quantiles. Missing values (`NA`s) are allowed.
`q` | vector of quantiles. Missing values (`NA`s) are allowed.
`p` | vector of probabilities. Missing values (`NA`s) are allowed.
`n` | number of random deviates to produce
`mean` | vector of linear predictors for the model. This is replicated to be the same length as `p`, `q` or `n`.
`scale` | vector of (positive) scale factors. This is replicated to be the same length as `p`, `q` or `n`.
`distribution` | character string giving the name of the distribution. This must be one of the elements of `survreg.distributions`
`parms` | optional parameters, if any, of the distribution. For the t-distribution this is the degrees of freedom.

### Details

Elements of `q` or `p` that are missing will cause the corresponding elements of the result to be missing.

The `location` and `scale` values are as they would be for `survreg`. The label "mean" was an unfortunate choice (made in mimicry of qnorm); since almost none of these distributions are symmetric it will not actually be a mean, but corresponds instead to the linear predictor of a fitted model. Translation to the usual parameterization found in a textbook is not always obvious. For example, the Weibull distribution is fit using the Extreme value distribution along with a log transformation. Letting F(t) = 1 - exp(-(at)^p) be the cumulative distribution of the Weibull using a standard parameterization in terms of a and p, the survreg location corresponds to -log(a) and the scale to 1/p (Kalbfleisch and Prentice, section 2.2.2).

### Value

density (`dsurvreg`), probability (`psurvreg`), quantile (`qsurvreg`), or for the requested distribution with mean and scale parameters `mean` and `sd`.

### References

Kalbfleisch, J. D. and Prentice, R. L. (1970). The Statistical Analysis of Failure Time Data Wiley, New York.

### See Also

`survreg`, `Normal`

### Examples

    # List of distributions available
    names(survreg.distributions)
    ## Not run:
     [1] "extreme"     "logistic"    "gaussian"    "weibull"     "exponential"
     [6] "rayleigh"    "loggaussian" "lognormal"   "loglogistic" "t"

    ## End(Not run)
    # Compare results
    all.equal(dsurvreg(1:10, 2, 5, dist='lognormal'), dlnorm(1:10, 2, 5))

    # Hazard function for a Weibull distribution
    x   <- seq(.1, 3, length=30)
    haz <- dsurvreg(x, 2, 3)/ (1-psurvreg(x, 2, 3))
    ## Not run:
    plot(x, haz, log='xy', ylab="Hazard") #line with slope (1/scale -1)

    ## End(Not run)

[Package survival version 3.2-7 Index]