These functions provide ways of working with a region: a data frame with numeric "left" and "right" columns, each row of which represents a unique finite interval (open, either type of half-open, or closed). Values of "left" and "right" columns should create an "ordered" set of intervals: left[1] <= right[1] <= left[2] <= right[2] <= ... (intervals with zero width are accepted). Originally, region_*() functions were designed to work with output of summ_hdr() and summ_interval(), but can be used for any data frame which satisfies the definition of a region.

region_is_in(region, x, left_closed = TRUE, right_closed = TRUE)

region_prob(region, f, left_closed = TRUE, right_closed = TRUE)

region_height(region, f, left_closed = TRUE, right_closed = TRUE)

region_width(region)

region_draw(region, col = "blue", alpha = 0.2)

Arguments

region

A data frame representing region.

x

Numeric vector to be tested for being inside region.

left_closed

A single logical value representing whether to treat left ends of intervals as their parts.

right_closed

A single logical value representing whether to treat right ends of intervals as their parts.

f

A pdqr-function.

col

Single color of rectangles to be used. Should be appropriate for col argument of col2rgb().

alpha

Single number representing factor modifying the opacity alpha; typically in [0; 1].

Value

region_is_in() returns a logical vector (with length equal to length of x) representing whether certain element of x is inside a region.

region_prob() returns a single number between 0 and 1 representing total probability of region.

region_height() returns a single number representing a height of a region with respect to f, i.e. minimum value that corresponding d-function can return based on relevant points inside a region.

region_width() returns a single number representing total width of a region.

region_draw() draws colored rectangles filling region intervals.

Details

region_is_in() tests each value of x for being inside interval. In other words, if there is a row for which element of x is between "left" and "right" value (respecting left_closed and right_closed options), output for that element will be TRUE. Note that for zero-width intervals one of left_closed or right_closed being TRUE is enough to accept that point as "in region".

region_prob() computes total probability of region according to pdqr-function f. If f has "discrete" type, output is computed as sum of probabilities for all "x" values from "x_tbl" metadata which lie inside a region (respecting left_closed and right_closed options while using region_is_in()). If f has "continuous" type, output is computed as integral of density over a region (*_closed options having any effect).

region_height() computes "height" of a region (with respect to f): minimum value of corresponding to f d-function can return based on relevant points inside a region. If f has "discrete" type, those relevant points are computed as "x" values from "x_tbl" metadata which lie inside a region (if there are no such points, output is 0). If f has "continuous" type, the whole intervals are used as relevant points. The notion of "height" comes from summ_hdr() function: if region is summ_hdr(f, level) for some level, then region_height(region, f) is what is called in summ_hdr()'s docs as "target height" of HDR. That is, a maximum value of d-function for which a set consisting from points at which d-function has values not less than target height and total probability of the set being not less than level.

region_width() computes total width of a region, i.e. sum of differences between "right" and "left" columns.

region_draw() draws (on current plot) intervals stored in region as colored rectangles vertically starting from zero and ending in the top of the plot (technically, at "y" value of 2e8).

See also

summ_hdr() for computing of Highest Density Region.

summ_interval() for computing of single interval summary of distribution.

Examples

# Type "discrete" d_binom <- as_d(dbinom, size = 10, prob = 0.7) hdr_dis <- summ_hdr(d_binom, level = 0.6) region_is_in(hdr_dis, 0:10)
#> [1] FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE FALSE
# This should be not less than 0.6 region_prob(hdr_dis, d_binom)
#> [1] 0.7004233
region_height(hdr_dis, d_binom)
#> [1] 0.2001209
region_width(hdr_dis)
#> [1] 2
# Type "continuous" d_norm <- as_d(dnorm) hdr_con <- summ_hdr(d_norm, level = 0.95) region_is_in(hdr_con, c(-Inf, -2, 0, 2, Inf))
#> [1] FALSE FALSE TRUE FALSE FALSE
# This should be approximately equal to 0.95 region_prob(hdr_con, d_norm)
#> [1] 0.9500426
# This should be equal to `d_norm(hdr_con[["left"]][1])` region_height(hdr_con, d_norm)
#> [1] 0.05840531
region_width(hdr_con)
#> [1] 3.920624
# Usage of `*_closed` options region <- data.frame(left = 1, right = 3) # Closed intervals region_is_in(region, 1:3)
#> [1] TRUE TRUE TRUE
# Open from left, closed from right region_is_in(region, 1:3, left_closed = FALSE)
#> [1] FALSE TRUE TRUE
# Closed from left, open from right region_is_in(region, 1:3, right_closed = FALSE)
#> [1] TRUE TRUE FALSE
# Open intervals region_is_in(region, 1:3, left_closed = FALSE, right_closed = FALSE)
#> [1] FALSE TRUE FALSE
# Handling of intervals with zero width region <- data.frame(left = 1, right = 1) # If at least one of `*_closed` options is `TRUE`, 1 will be considered as # "in a region" region_is_in(region, 1)
#> [1] TRUE
region_is_in(region, 1, left_closed = FALSE)
#> [1] TRUE
region_is_in(region, 1, right_closed = FALSE)
#> [1] TRUE
# Only this will return `FALSE` region_is_in(region, 1, left_closed = FALSE, right_closed = FALSE)
#> [1] FALSE
# Drawing d_mix <- form_mix(list(as_d(dnorm), as_d(dnorm, mean = 5))) plot(d_mix)
region_draw(summ_hdr(d_mix, 0.95))