# pnbeta

From DPQ v0.3-3
0th

Percentile

##### Noncentral Beta Probabilities

pnbetaAppr2() and its inital version pnbetaAppr2v1() provide the “approximation 2” of Chattamvelli and Shanmugam(1997) to the noncentral Beta probability distribution.

pnbetaAS310() is an R level interface to a C translation (and “Rification”) of the AS 310 Fortran implementation.

Keywords
distribution, math
##### Usage

pnbetaAppr2(x, a, b, ncp = 0, lower.tail = TRUE, log.p = FALSE)
##### Arguments
x

numeric vector (of quantiles), typically from inside $[0,1]$.

a, b

the shape parameters of Beta, aka as shape1 and shape2.

ncp

non-centrality parameter.

log.p

logical; if TRUE, probabilities p are given as log(p).

lower.tail

logical; if TRUE (default), probabilities are $P[X \le x]$, otherwise, $P[X > x]$.

##### Value

a numeric vector of (log) probabilities of the same length as x.

##### Note

The authors in the reference compare AS 310 with Frick(1990) and Lenth(1987) and state to be better than both. R's current (2019) noncentral beta implementation builds on Lenth(1987), with some amendments though; still, pnbetaAS310() may potentially be better, at least in certain corners of the 4-dimensional input space.

##### References

Chattamvelli, R., and Shanmugam, R. (1997) Algorithm AS 310: Computing the Non-Central Beta Distribution Function. Journal of the Royal Statistical Society. Series C (Applied Statistics) 46(1), 146--156, for “approximation 2” notably p.154; 10.1111/1467-9876.00055.

##### See Also

R's own pbeta.

##### Aliases
• pnbetaAppr2
• pnbetaAppr2v1
• pnbetaAS310
##### Examples
# NOT RUN {
## Same arguments as for Table 1 (p.151) of the reference
a <- 5*rep(1:3, each=3)
aargs <- cbind(a = a, b = a,
ncp = rep(c(54, 140, 170), 3),
x = 1e-4*c(8640, 9000, 9560, 8686, 9000, 9000, 8787, 9000, 9220))
aargs
pnbA2 <- apply(aargs, 1, function(aa) do.call(pnbetaAppr2, as.list(aa)))
pnA310<- apply(aargs, 1, function(aa) do.call(pnbetaAS310, as.list(aa)))
aar2 <- aargs; dimnames(aar2)[[2]] <- c(paste0("shape", 1:2), "ncp", "q")
pnbR  <- apply(aar2,  1, function(aa) do.call(pbeta, as.list(aa)))
range(relD2   <- 1 - pnbA2 /pnbR)
range(relD310 <- 1 - pnA310/pnbR)
cbind(aargs, pnbA2, pnA310, pnbR,
relD2 = signif(relD2, 3), relD310 = signif(relD310, 3)) # <------> Table 1
stopifnot(abs(relD2)   < 0.009) # max is 0.006286
stopifnot(abs(relD310) < 1e-5 ) # max is 6.3732e-6

## Arguments as for Table 2 (p.152) of the reference :
aarg2 <- cbind(a = c( 10, 10, 15, 20, 20, 20, 30, 30),
b = c( 20, 10,  5, 10, 30, 50, 20, 40),
ncp=c(150,120, 80,110, 65,130, 80,130),
x = c(868,900,880,850,660,720,720,800)/1000)
pnbA2 <- apply(aarg2, 1, function(aa) do.call(pnbetaAppr2, as.list(aa)))
pnA310<- apply(aarg2, 1, function(aa) do.call(pnbetaAS310, as.list(aa)))
aar2 <- aarg2; dimnames(aar2)[[2]] <- c(paste0("shape", 1:2), "ncp", "q")
pnbR  <- apply(aar2,  1, function(aa) do.call(pbeta, as.list(aa)))
range(relD2   <- 1 - pnbA2 /pnbR)
range(relD310 <- 1 - pnA310/pnbR)
cbind(aarg2, pnbA2, pnA310, pnbR,
relD2 = signif(relD2, 3), relD310 = signif(relD310, 3)) # <------> Table 2
stopifnot(abs(relD2  ) < 0.006) # max is 0.00412
stopifnot(abs(relD310) < 1e-5 ) # max is 5.5953e-6

## Arguments as for Table 3 (p.152) of the reference :
aarg3 <- cbind(a = c( 10, 10, 10, 15, 10, 12, 30, 35),
b = c(  5, 10, 30, 20,  5, 17, 30, 30),
ncp=c( 20, 54, 80,120, 55, 64,140, 20),
x = c(644,700,780,760,795,560,800,670)/1000)
pnbA3 <- apply(aarg3, 1, function(aa) do.call(pnbetaAppr2, as.list(aa)))
pnA310<- apply(aarg3, 1, function(aa) do.call(pnbetaAS310, as.list(aa)))
aar3 <- aarg3; dimnames(aar3)[[2]] <- c(paste0("shape", 1:2), "ncp", "q")
pnbR  <- apply(aar3,  1, function(aa) do.call(pbeta, as.list(aa)))
range(relD2   <- 1 - pnbA3 /pnbR)
range(relD310 <- 1 - pnA310/pnbR)
cbind(aarg3, pnbA3, pnA310, pnbR,
relD2 = signif(relD2, 3), relD310 = signif(relD310, 3)) # <------> Table 3
stopifnot(abs(relD2  ) < 0.09) # max is 0.06337
stopifnot(abs(relD310) < 1e-4) # max is 3.898e-5

# }

Documentation reproduced from package DPQ, version 0.3-3, License: GPL (>= 2)

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