Description Usage Arguments Details Value Author(s) References See Also Examples
Density, distribution function, quantile function, and random generation for the log logistic.
1 2 3 4 |
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
location, scale |
location and scale parameters (non-negative numeric). |
lower.tail |
logical; if |
log, log.p |
logical; if |
If location
or scale
are omitted, they assume the
default values of 0 and 1 respectively.
The log-Logistic distribution with location = m
and scale
= s
has distribution function
F(x) = 1 / (1 + exp(-(log(x)-m)/s))
and density
f(x) = 1/(s*x) exp(-(log(x)-m)/s) (1 + exp(-(log(x)-m)/s))^-2.
dllogis
gives the density, pllogis
gives the
distribution function, qllogis
gives the quantile function
and rllogis
generates random deviates.
Christophe Pouzat christophe.pouzat@gmail.com
Lindsey, J.K. (2004) Introduction to Applied Statistics: A Modelling Approach. OUP.
Lindsey, J.K. (2004) The Statistical Analysis of Stochastic Processes in Time. CUP.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## Not run:
tSeq <- seq(0.001,0.6,0.001)
location.true <- -2.7
scale.true <- 0.025
Yd <- dllogis(tSeq, location.true, scale.true)
Yh <- hllogis(tSeq, location.true, scale.true)
max.Yd <- max(Yd)
max.Yh <- max(Yh)
Yd <- Yd / max.Yd
Yh <- Yh / max.Yh
oldpar <- par(mar=c(5,4,4,4))
plot(tSeq, Yd, type="n", axes=FALSE, ann=FALSE,
xlim=c(0,0.6), ylim=c(0,1))
axis(2,at=seq(0,1,0.2),labels=round(seq(0,1,0.2)*max.Yd,digits=2))
mtext("Density (1/s)", side=2, line=3)
axis(1,at=pretty(c(0,0.6)))
mtext("Time (s)", side=1, line=3)
axis(4, at=seq(0,1,0.2), labels=round(seq(0,1,0.2)*max.Yh,digits=2))
mtext("Hazard (1/s)", side=4, line=3, col=2)
mtext("Log Logistic Density and Hazard Functions", side=3, line=2,cex=1.5)
lines(tSeq,Yd)
lines(tSeq,Yh,col=2)
par(oldpar)
## End(Not run)
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