plot(Binom(size = 4, prob = 0.3))
plot(Binom(size = 4, prob = 0.3), do.points = FALSE)
plot(Binom(size = 4, prob = 0.3), verticals = FALSE)
plot(Binom(size = 4, prob = 0.3), main = TRUE)
plot(Binom(size = 4, prob = 0.3), main = FALSE)
plot(Binom(size = 4, prob = 0.3), cex.points = 1.2, pch = 20)
B <- Binom(size = 4, prob = 0.3)
plot(B, col = "red", col.points = "green", main = TRUE, col.main = "blue",
col.sub = "orange", sub = TRUE, cex.sub = 0.6, col.inner = "brown")
plot(Nbinom(size = 4,prob = 0.3), cex.points = 1.2, col = "red",
col.points = "green")
plot(Nbinom(size = 4,prob = 0.3), cex.points = 1.2, pch.u = 20, pch.a = 10)
plot(Norm(), main = TRUE, cex.main = 3, tmar = 6)
plot(Norm(), inner = FALSE, main = TRUE, cex.main = 3, tmar = 6)
plot(Norm(), lwd = 3, col = "red", ngrid = 200, lty = 3, las = 2)
plot(Norm(), main = "my Distribution: %A",
inner = list(expression(paste(lambda,"-density of %C(%P)")), "CDF",
"Pseudo-inverse with param's %N"),
sub = "this plot was correctly generated on %D",
cex.inner = 0.9, cex.sub = 0.8)
plot(Cauchy())
plot(Cauchy(), xlim = c(-4,4))
plot(Chisq())
plot(Chisq(), log = "xy", ngrid = 100)
Ch <- Chisq(); setgaps(Ch); plot(Ch, do.points = FALSE)
setgaps(Ch, exactq = 3); plot(Ch, verticals = FALSE)
plot(Ch, cex = 1.2, pch.u = 20, pch.a = 10, col.points = "green",
col.vert = "red")
## some distribution with gaps
wg <- flat.mix(UnivarMixingDistribution(Unif(0,1),Unif(4,5),
withSimplify=FALSE))
# some Lebesgue decomposed distribution
mymix <- UnivarLebDecDistribution(acPart = wg, discretePart = Binom(4,.4),
acWeight = 0.4)
plot(mymix)
Run the code above in your browser using DataLab