Struct bio::stats::bayesian::bayes_factors::BayesFactor
source · pub struct BayesFactor(pub f64);
Expand description
A newtype for Bayes factors.
Tuple Fields
0: f64
Implementations
sourceimpl BayesFactor
impl BayesFactor
sourcepub fn evidence_kass_raftery(&self) -> KassRaftery
pub fn evidence_kass_raftery(&self) -> KassRaftery
Calculate strength of evidence as defined by Kass and Raftery 1995.
Methods from Deref<Target = f64>
pub const RADIX: u32 = 2u32
pub const MANTISSA_DIGITS: u32 = 53u32
pub const DIGITS: u32 = 15u32
pub const EPSILON: f64 = 2.2204460492503131E-16f64
pub const MIN: f64 = -1.7976931348623157E+308f64
pub const MIN_POSITIVE: f64 = 2.2250738585072014E-308f64
pub const MAX: f64 = 1.7976931348623157E+308f64
pub const MIN_EXP: i32 = -1_021i32
pub const MAX_EXP: i32 = 1_024i32
pub const MIN_10_EXP: i32 = -307i32
pub const MAX_10_EXP: i32 = 308i32
pub const NAN: f64 = NaNf64
pub const INFINITY: f64 = +Inff64
pub const NEG_INFINITY: f64 = -Inff64
1.62.0 · sourcepub fn total_cmp(&self, other: &f64) -> Ordering
pub fn total_cmp(&self, other: &f64) -> Ordering
Return the ordering between self
and other
.
Unlike the standard partial comparison between floating point numbers,
this comparison always produces an ordering in accordance to
the totalOrder
predicate as defined in the IEEE 754 (2008 revision)
floating point standard. The values are ordered in the following sequence:
- negative quiet NaN
- negative signaling NaN
- negative infinity
- negative numbers
- negative subnormal numbers
- negative zero
- positive zero
- positive subnormal numbers
- positive numbers
- positive infinity
- positive signaling NaN
- positive quiet NaN.
The ordering established by this function does not always agree with the
PartialOrd
and PartialEq
implementations of f64
. For example,
they consider negative and positive zero equal, while total_cmp
doesn’t.
The interpretation of the signaling NaN bit follows the definition in the IEEE 754 standard, which may not match the interpretation by some of the older, non-conformant (e.g. MIPS) hardware implementations.
Example
struct GoodBoy {
name: String,
weight: f64,
}
let mut bois = vec![
GoodBoy { name: "Pucci".to_owned(), weight: 0.1 },
GoodBoy { name: "Woofer".to_owned(), weight: 99.0 },
GoodBoy { name: "Yapper".to_owned(), weight: 10.0 },
GoodBoy { name: "Chonk".to_owned(), weight: f64::INFINITY },
GoodBoy { name: "Abs. Unit".to_owned(), weight: f64::NAN },
GoodBoy { name: "Floaty".to_owned(), weight: -5.0 },
];
bois.sort_by(|a, b| a.weight.total_cmp(&b.weight));
Trait Implementations
sourceimpl Clone for BayesFactor
impl Clone for BayesFactor
sourcefn clone(&self) -> BayesFactor
fn clone(&self) -> BayesFactor
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresourceimpl Debug for BayesFactor
impl Debug for BayesFactor
sourceimpl Deref for BayesFactor
impl Deref for BayesFactor
sourceimpl From<BayesFactor> for f64
impl From<BayesFactor> for f64
sourcefn from(v: BayesFactor) -> Self
fn from(v: BayesFactor) -> Self
sourceimpl From<f64> for BayesFactor
impl From<f64> for BayesFactor
sourceimpl PartialEq<BayesFactor> for BayesFactor
impl PartialEq<BayesFactor> for BayesFactor
sourcefn eq(&self, other: &BayesFactor) -> bool
fn eq(&self, other: &BayesFactor) -> bool
sourceimpl PartialOrd<BayesFactor> for BayesFactor
impl PartialOrd<BayesFactor> for BayesFactor
sourcefn partial_cmp(&self, other: &BayesFactor) -> Option<Ordering>
fn partial_cmp(&self, other: &BayesFactor) -> Option<Ordering>
1.0.0 · sourcefn le(&self, other: &Rhs) -> bool
fn le(&self, other: &Rhs) -> bool
self
and other
) and is used by the <=
operator. Read more