Quantile Function Approximation
q_approxfun is a generic function that for a given object generates function to approximate the quantile function.
q_approxfun(O, range = q(O, c(0.005, 0.995)), n = 1000) ## S3 method for class 'dist' q_approxfun(O, range = q(O, c(0.005, 0.995)), n = 1000)
O |
distribution object. |
range |
interval on which the grid is defined, q(O, c(0.005, 0.995)). |
n |
number of points within the grid, default: 1000. |
Function q_approxfun generates a grid of values on which the CDF of the object is evaluated.
The function returns a quantile function that uses approx and the values
of the grid to approximate the quantiles. This function is designed mostly for the mixture distributions
where the standard q method may be slow and thus allows to trade the accuracy for the speed.
The returned function takes the arguments p, lower.tail and log.p, see q.
Function.
N <- normdist(1, 3) N2 <- normdist(8, 3) M <- mixdist(N, N2, weights = c(0.5, 0.5)) q_app <- q_approxfun(M) q_app(c(.2, .5, .7)) q_app(c(.2, .5, .7), lower.tail = FALSE)
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