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)
Same interpretation as in
The shape parameter value c described in in
The details are given in
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
plog(), if argument
q contains large values
q is long in length
then the memory requirements may be very high.
Very large values in
q are handled by an approximation by
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=PDF; orange=CDF") lines(x + 0.1, plog(x, shape), col = "orange", lty = 3, type = "h") ## End(Not run)
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