Logarithmic Distribution
Density, distribution function, quantile function, and random generation for the logarithmic distribution.
dlog(x, shape, log = FALSE) plog(q, shape, lower.tail = TRUE, log.p = FALSE) qlog(p, shape) rlog(n, shape)
The details are given in logff.
dlog gives the density,
plog gives the distribution function,
qlog gives the quantile function, and
rlog generates random deviates.
Given some response data, the VGAM family function
logff estimates the parameter shape.
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).
T. W. Yee
Forbes, C., Evans, M., Hastings, N. and Peacock, B. (2011). Statistical Distributions, Hoboken, NJ, USA: John Wiley and Sons, Fourth edition.
dlog(1:20, 0.5)
rlog(20, 0.5)
## Not run: shape <- 0.8; x <- 1:10
plot(x, dlog(x, shape = shape), type = "h", ylim = 0:1,
sub = "shape=0.8", las = 1, col = "blue", ylab = "shape",
main = "Logarithmic distribution: blue=density; orange=distribution function")
lines(x + 0.1, plog(x, shape = shape), col = "orange", lty = 3, type = "h")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.