Log {VGAM} | R Documentation

## Logarithmic Distribution

### Description

Density, distribution function, and random generation for the logarithmic distribution.

### Usage

    dlog(x, prob, log = FALSE)
    plog(q, prob, log.p = FALSE)
    rlog(n, prob, Smallno = 1.0e-6)

### Arguments

`x, q` | Vector of quantiles. For the density, it should be a vector with positive integer values in order for the probabilities to be positive.

`n` | number of observations. Same as in `runif`.
`prob` | The parameter value c described in in `logff`. Here it is called `prob` because 0<c<1 is the range. For `rlog()` this parameter must be of length 1.
`log, log.p` | Logical. If `log.p = TRUE` then all probabilities `p` are given as `log(p)`.
`Smallno` | Numeric, a small value used by the rejection method for determining the upper limit of the distribution. That is, `plog(U, prob) > 1-Smallno` where `U` is the upper limit.

### Details

The details are given in `logff`.

### Value

`dlog` gives the density, `plog` gives the distribution function, and `rlog` generates random deviates.

### Note

Given some response data, the VGAM family function `logff` estimates the parameter `prob`. For `plog()`, if argument `q` contains large values and/or `q` is long in length then the memory requirements may be very high. Very large values in `q` are handled by an approximation by Owen (1965).

### Author(s)

T. W. Yee

### References

Forbes, C., Evans, M., Hastings, N. and Peacock, B. (2011) Statistical Distributions, Hoboken, NJ, USA: John Wiley and Sons, Fourth edition.

### See Also

`logff`.

### Examples

    dlog(1:20, 0.5)
    rlog(20, 0.5)

    ## Not run:  prob <- 0.8; x <- 1:10
    plot(x, dlog(x, prob = prob), type = "h", ylim = 0:1,
         sub = "prob=0.8", las = 1, col = "blue", ylab = "Probability",
         main = "Logarithmic distribution: blue=density; orange=distribution function")
    lines(x + 0.1, plog(x, prob = prob), col = "orange", lty = 3, type = "h")
    ## End(Not run)

[Package VGAM version 1.0-1 Index]