Liland.test: A test for over represented short distances in the Liland...

In fixedTimeEvents: The Distribution of Distances Between Discrete Events in Fixed Time

Description

A binomial test is performed using probabilites from the Liland distribution to check if the number of distances shorter to or equal to xlim are significantly higher than the expected value. Critical value and power are supplied as separate functions.

Usage

Liland.test(y, xlim, R, r)
## S3 method for class 'Ltest'
print(x, ...)
## S3 method for class 'Ltest'
summary(object, ...)
Liland.crit(xlim, R, r, alpha = 0.05)
Liland.pow(xlim, R, r, y = 1:(r-1), alpha = 0.05)

Arguments

y	The number of observed short distances.
xlim	The maximum distance that is seen as short.
R	The number of trials.
r	The number of successes.
alpha	Significance level.
x	The object to printed.
object	The object to be summarized.
...	Additional arguments for print and summary (not used).

Value

Liland.test returns a named vector of P-values with class Ltest. The other methods only print.

References

Liland, KH & Snipen, L, FixedTimeEvents: An R package for the distribution of distances between discrete events in fixed time, SoftwareX 5 (2016).

See Also

dLiland, Liland, simLiland

Examples

Lt <- Liland.test(12,1,1949,162)
print(Lt)
summary(Lt)

# Critical value
Liland.crit(1, 1949, 162) 

# Power
plot(Liland.pow(1,1949,161, alpha = 0.05), type = 'l', xlab = '#(x<2)', ylab = 'power')

Example output

P-value for H0: y > E(Y)
       12 
0.5846628 
R = 1949, r = 162, xlim = 1
E(Y) = 13.38225

P-value for H0: y > E(Y)
       12 
0.5846628 
[1] 19

fixedTimeEvents documentation built on Jan. 4, 2022, 5:09 p.m.