## gamma-2.R
## PJ Feb 14, 2002 / 2014-08-07
## This is a template showing how to create a
## variable 10 different samples and show 10
## histograms on one page.
## Try this program a few times. Vary the "sampleSize"
## to observe any changes.
sh <- 1
sc <- 5
sampleSize <- 40
## Suppose you want to generate 10 distributions
## and display them in a single picture
## Keep a copy of the old par settings
op <- par(no.readonly = TRUE)
SAVEME <- FALSE
if (SAVEME) pdf(file = "distributions-gamma-02-1.pdf", width = 8.5,
height = 10, onefile = FALSE, family = "Times", paper = "special")
par(mfrow=c(5,2))
createDist <-function(i){
z <- rgamma(sampleSize, shape=sh, scale=sc)
hist(z, breaks=10)
}
lapply(1:10,createDist)
## [[1]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16
##
## $counts
## [1] 21 8 4 3 0 1 1 2
##
## $density
## [1] 0.2625 0.1000 0.0500 0.0375 0.0000 0.0125 0.0125 0.0250
##
## $mids
## [1] 1 3 5 7 9 11 13 15
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[2]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16
##
## $counts
## [1] 14 9 2 6 2 3 2 2
##
## $density
## [1] 0.1750 0.1125 0.0250 0.0750 0.0250 0.0375 0.0250 0.0250
##
## $mids
## [1] 1 3 5 7 9 11 13 15
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[3]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20 22
##
## $counts
## [1] 15 8 8 1 2 2 1 1 1 0 1
##
## $density
## [1] 0.1875 0.1000 0.1000 0.0125 0.0250 0.0250 0.0125 0.0125 0.0125 0.0000
## [11] 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19 21
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[4]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20
##
## $counts
## [1] 9 12 9 1 3 1 1 2 1 1
##
## $density
## [1] 0.1125 0.1500 0.1125 0.0125 0.0375 0.0125 0.0125 0.0250 0.0125 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[5]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20 22
##
## $counts
## [1] 7 13 2 2 4 4 1 1 2 3 1
##
## $density
## [1] 0.0875 0.1625 0.0250 0.0250 0.0500 0.0500 0.0125 0.0125 0.0250 0.0375
## [11] 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19 21
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[6]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20
##
## $counts
## [1] 15 9 4 4 3 0 3 0 0 2
##
## $density
## [1] 0.1875 0.1125 0.0500 0.0500 0.0375 0.0000 0.0375 0.0000 0.0000 0.0250
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[7]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20 22
##
## $counts
## [1] 8 8 4 11 3 0 2 0 1 2 1
##
## $density
## [1] 0.1000 0.1000 0.0500 0.1375 0.0375 0.0000 0.0250 0.0000 0.0125 0.0250
## [11] 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19 21
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[8]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18
##
## $counts
## [1] 20 9 3 3 2 0 2 0 1
##
## $density
## [1] 0.2500 0.1125 0.0375 0.0375 0.0250 0.0000 0.0250 0.0000 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[9]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20 22 24 26
##
## $counts
## [1] 11 9 7 4 2 2 2 1 0 0 0 1 1
##
## $density
## [1] 0.1375 0.1125 0.0875 0.0500 0.0250 0.0250 0.0250 0.0125 0.0000 0.0000
## [11] 0.0000 0.0125 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19 21 23 25
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
##
## [[10]]
## $breaks
## [1] 0 2 4 6 8 10 12 14 16 18 20
##
## $counts
## [1] 9 9 7 6 4 3 0 0 1 1
##
## $density
## [1] 0.1125 0.1125 0.0875 0.0750 0.0500 0.0375 0.0000 0.0000 0.0125 0.0125
##
## $mids
## [1] 1 3 5 7 9 11 13 15 17 19
##
## $xname
## [1] "z"
##
## $equidist
## [1] TRUE
##
## attr(,"class")
## [1] "histogram"
if (SAVEME) dev.off()
par(op)