powen {OwenQ} | R Documentation |
Owen distribution functions when δ1>δ2
Description
Evaluates the Owen distribution functions when the noncentrality parameters satisfy δ1>δ2 and the number of degrees of freedom is integer.
-
powen1
evaluates P(T1 ≤ t1, T2 ≤ t2) (Owen's equality 8) -
powen2
evaluates P(T1 ≤ t1, T2 > t2) (Owen's equality 9) -
powen3
evaluates P(T1 > t1, T2 > t2) (Owen's equality 10) -
powen4
evaluates P(T1 > t1, T2 ≤ t2) (Owen's equality 11)
Usage
powen1(nu, t1, t2, delta1, delta2, algo = 2)
powen2(nu, t1, t2, delta1, delta2, algo = 2)
powen3(nu, t1, t2, delta1, delta2, algo = 2)
powen4(nu, t1, t2, delta1, delta2, algo = 2)
Arguments
nu |
integer greater than |
t1 , t2 |
two numbers, positive or negative, possible infinite |
delta1 , delta2 |
two vectors of possibly infinite numbers with the same length,
the noncentrality parameters;
must satisfy |
algo |
the algorithm used, |
Value
A vector of numbers between 0
and 1
, possibly
containing some NaN
.
Note
When the number of degrees of freedom is odd, the procedure resorts to
the Owen T-function (OwenT
).
References
Owen, D. B. (1965). A special case of a bivariate noncentral t-distribution. Biometrika 52, 437-446.
See Also
Use psbt
for general values of delta1
and delta2
.
Examples
nu=5; t1=2; t2=1; delta1=3; delta2=2
# Wolfram integration gives 0.1394458271284726
( p1 <- powen1(nu, t1, t2, delta1, delta2) )
# Wolfram integration gives 0.0353568969628651
( p2 <- powen2(nu, t1, t2, delta1, delta2) )
# Wolfram integration gives 0.806507459306199
( p3 <- powen3(nu, t1, t2, delta1, delta2) )
# Wolfram integration gives 0.018689824158
( p4 <- powen4(nu, t1, t2, delta1, delta2) )
# the sum should be 1
p1+p2+p3+p4