This small package contains the Liland distribution for distances between discrete events in fixed time with probability mass, cumulative distribution, quantile function, random number generator, simulation functions and a test for over representation of short distances.
An example of its use is found in bacterial gene regulation where genes along a chromosome are regulated or not regulated. One may ask if the distances between regulated genes are random or tend to cluster, e.g. as operons. In the following example we have $R=1949$ genes (trials) of which $r=162$ are regulated (success).
library(fixedTimeEvents) R <- 1949; r <- 162 Liland(R, r)
R <- 1949; r <- 162 dL <- dLiland(1:100, R, r) plot(dL, type = 'l', xlab = "distance", ylab = "probability mass")
A test for over representation of short distances can be performed, e.g. for distances shorter than 2 ($x<2$).
Lt <- Liland.test(1:100, 1, R, r) Liland.crit(1, R, r) plot(Lt, type='l', xlab='#(x<2)', ylab='p-value') points(73, Liland.test(73, 1, R, r), col = 2)
A comparison between distances obtained from sampling from the Bernoulli distribution with a fixed number of successes and the theoretical values from the Liland distribution follows.
sL <- simLiland(5000, 15,5) # 5000 samples, R = 15, r = 5 qqplot(dLiland(1:length(sL),15,5),sL, xlab='F(x;15,5)', ylab='Sample (5000)') abline(0,1, lty=2, col=2)
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