Modify support of pdqr-function using method of choice.

form_resupport(f, support, method = "reflect")



A pdqr-function.


Numeric vector with two increasing (or non-decreasing, see Details) elements describing support of the output. Values can be NA, in which case corresponding edge(s) are taken from f's support.


Resupport method. One of "reflect", "trim", "winsor", "linear".


A pdqr-function with modified support and the same class and type as f.


Method "reflect" takes a density "tails" to the left of support[1] and to the right of support[2] and reflects them inside support. It means that values of density inside and outside of supplied support are added together in "symmetric fashion": d(x) = d_f(x) + d_f(l - (x-l)) + d_f(r + (r-x)), where d_f is density of input, d is density of output, l and r are left and right edges of input support. This option is useful for repairing support of new_*()'s output, as by default kernel density estimation in density() adds tails to the range of input x values. For example, if there is a need to ensure that distribution has only positive values, one can do form_resupport(f, c(0, NA), method = "reflect"). Notes:

  • For "discrete" pdqr-functions that might result into creating new "x" values of distribution.

  • Reflection over support[1] is done only if it is strictly greater than f's left edge of support. Reflection over support[2] - if f's right edge is strictly smaller.

Method "trim" removes density "tails" outside of support, normalizes the rest and creates appropriate pdqr-function.

Method "winsor" makes all density "tails" outside of input support "squashed" inside it in "dirac-like" fashion. It means that probability from both tails is moved inside support and becomes concentrated in 1e-8 neighborhood of nearest edge. This models a singular dirac distributions at the edges of support. Note that support can represent single point, in which case output has single element if f's type is "discrete" or is a dirac-like distribution in case of "continuous" type.

Method "linear" transforms f's support linearly to be input support. For example, if f's support is [0; 1] and support is c(-1, 1), linear resupport is equivalent to 2*f - 1. Note that support can represent single point with the same effect as in "winsor" method.

See also

form_regrid() for changing grid (rows of "x_tbl" metadata) of pdqr-function.

form_retype() for changing type of pdqr-function.

Other form functions: form_estimate(), form_mix(), form_regrid(), form_retype(), form_smooth(), form_tails(), form_trans()


set.seed(101) d_norm <- as_d(dnorm) d_dis <- new_d(data.frame(x = 1:4, prob = 1:4 / 10), "discrete") # Method "reflect" plot(d_norm)
lines(form_resupport(d_norm, c(-2, 1.5), "reflect"), col = "blue")
# For "discrete" functions it might create new values meta_x_tbl(form_resupport(d_dis, c(NA, 2.25), "reflect"))
#> x prob cumprob #> 1 1.0 0.1666667 0.1666667 #> 2 1.5 0.5000000 0.6666667 #> 3 2.0 0.3333333 1.0000000
# This is often useful to ensure constraints after `new_()` x <- runif(1e4) d_x <- new_d(x, "continuous") plot(d_x)
lines(form_resupport(d_x, c(0, NA), "reflect"), col = "red")
lines(form_resupport(d_x, c(0, 1), "reflect"), col = "blue")
# Method "trim" plot(d_norm)
lines(form_resupport(d_norm, c(-2, 1.5), "trim"), col = "blue")
# Method "winsor" plot(d_norm)
lines(form_resupport(d_norm, c(-2, 1.5), "winsor"), col = "blue")
# Method "linear" plot(d_norm)
lines(form_resupport(d_norm, c(-2, 1.5), "linear"), col = "blue")