[−][src]Trait rstats::RStats

pub trait RStats {
    fn amean(&self) -> Result<f64>;

    fn ameanstd(&self) -> Result<MStats>;

    fn awmean(&self) -> Result<f64>;

    fn awmeanstd(&self) -> Result<MStats>;
}

Required methods

fn amean(&self) -> Result<f64>

fn ameanstd(&self) -> Result<MStats>

fn awmean(&self) -> Result<f64>

fn awmeanstd(&self) -> Result<MStats>

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Implementations on Foreign Types

impl RStats for Vec<i64>[src]

fn amean(&self) -> Result<f64>[src]

Arithmetic mean of an i64 slice

Example

use rstats::RStats;
let v1 = vec![1_i64,2,3,4,5,6,7,8,9,10,11,12,13,14];
assert_eq!(v1.amean().unwrap(),7.5_f64);

fn ameanstd(&self) -> Result<MStats>[src]

Arithmetic mean and standard deviation of an i64 slice

Example

use rstats::RStats;
let v1 = vec![1_i64,2,3,4,5,6,7,8,9,10,11,12,13,14];
let res = v1.ameanstd().unwrap();
assert_eq!(res.mean,7.5_f64);
assert_eq!(res.std,4.031128874149275_f64);

fn awmean(&self) -> Result<f64>[src]

Linearly weighted arithmetic mean of an i64 slice.
Linearly descending weights from n down to one.
Time dependent data should be in the stack order - the last being the oldest.

Example

use rstats::RStats;
let v1 = vec![1_i64,2,3,4,5,6,7,8,9,10,11,12,13,14];
assert_eq!(v1.awmean().unwrap(),5.333333333333333_f64);

fn awmeanstd(&self) -> Result<MStats>[src]

Liearly weighted arithmetic mean and standard deviation of an i64 slice.
Linearly descending weights from n down to one.
Time dependent data should be in the stack order - the last being the oldest.

Example

use rstats::RStats;
let v1 = vec![1_i64,2,3,4,5,6,7,8,9,10,11,12,13,14];
let res = v1.awmeanstd().unwrap();
assert_eq!(res.mean,5.333333333333333_f64);
assert_eq!(res.std,3.39934634239519_f64);

impl RStats for Vec<f64>[src]

fn amean(&self) -> Result<f64>[src]

Arithmetic mean of an f64 slice

Example

use rstats::RStats;
let v1 = vec![1_f64,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.];
assert_eq!(v1.amean().unwrap(),7.5_f64);

fn ameanstd(&self) -> Result<MStats>[src]

Arithmetic mean and standard deviation of an f64 slice

Example

use rstats::RStats;
let v1 = vec![1_f64,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.];
let res = v1.ameanstd().unwrap();
assert_eq!(res.mean,7.5_f64);
assert_eq!(res.std,4.031128874149275_f64);

fn awmean(&self) -> Result<f64>[src]

Linearly weighted arithmetic mean of an i64 slice.
Linearly descending weights from n down to one.
Time dependent data should be in the stack order - the last being the oldest.

Example

use rstats::RStats;
let v1 = vec![1_f64,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.];
assert_eq!(v1.awmean().unwrap(),5.333333333333333_f64);

fn awmeanstd(&self) -> Result<MStats>[src]

Liearly weighted arithmetic mean and standard deviation of an i64 slice.
Linearly descending weights from n down to one.
Time dependent data should be in the stack order - the last being the oldest.

Example

use rstats::RStats;
let v1 = vec![1_f64,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.];
let res = v1.awmeanstd().unwrap();
assert_eq!(res.mean,5.333333333333333_f64);
assert_eq!(res.std,3.39934634239519_f64);
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Implementors

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