| summ_pval {pdqr} | R Documentation |
Summarize distribution with p-value
Description
summ_pval() computes p-value(s) based on supplied distribution and observed
value(s). There are several methods of computing p-values ("both", "right",
and "left") as well as several types of multiple comparison adjustments
(using on stats::p.adjust()).
Usage
summ_pval(f, obs, method = "both", adjust = "holm")
Arguments
f |
A pdqr-function representing distribution. |
obs |
Numeric vector of observed values to be used as threshold for p-value. Can have multiple values, in which case output will be adjusted for multiple comparisons with p.adjust(). |
method |
Method representing direction of p-value computation. Should be one of "both", "right", "left". |
adjust |
Adjustment method as |
Details
Method "both" for each element in obs computes two-sided p-value
as min(1, 2 * min(right_p_val, left_p_val)), where right_p_val and
left_p_val are right and left one-sided p-values (ones which are computed
with "right" and "left" methods) of obs's elements correspondingly.
Method "right" for each element x of obs computes probability of f >= x
being true (more strictly, of random variable, represented by f, being not
less than x). This corresponds to right one-sided p-value.
Method "left" for each element x of obs computes probability of f <= x,
which is a left one-sided p-value.
Note that by default multiple p-values in output are adjusted with
p.adjust(*, method = adjust). To not do any adjustment, use adjust = "none".
Value
A numeric vector with the same length as obs representing
corresponding p-values after possible adjustment for multiple comparisons.
See Also
Other summary functions:
summ_center(),
summ_classmetric(),
summ_distance(),
summ_entropy(),
summ_hdr(),
summ_interval(),
summ_moment(),
summ_order(),
summ_prob_true(),
summ_quantile(),
summ_roc(),
summ_separation(),
summ_spread()
Examples
# Type "discrete"
d_dis <- new_d(data.frame(x = 1:5, prob = c(1, 2, 3, 2, 1) / 9), "discrete")
summ_pval(d_dis, 3, method = "both")
summ_pval(d_dis, 3, method = "right")
summ_pval(d_dis, 3, method = "left")
# Type "continuous"
d_norm <- as_d(dnorm)
summ_pval(d_norm, 2, method = "both")
summ_pval(d_norm, 2, method = "right")
summ_pval(d_norm, 2, method = "left")
# Adjustment is made for multiple observed values
summ_pval(d_norm, seq(0, 2, by = 0.1))
## Use `adjust = "none"` for to not do any adjustment
summ_pval(d_norm, seq(0, 2, by = 0.1), adjust = "none")