Struct forrust::prediction::dumb::Dumb[−][src]

pub struct Dumb { /* fields omitted */ }

Takes an exponential smoothing and makes a dumb prediction of the next season This uses an algorithm i made up myself that takes to account the distances the exponential smoothing for each month relative to the linear regresion of a time series and calculates a growth factor thats ‘a prediction’ of the signal for the future, and thats when i use a random value to add some noise

Implementations

impl Dumb[src]

pub fn new(time_series: &TimeSeries) -> Self[src]

pub fn with_season(self, season: usize) -> Self[src]

Sets the length of the season its a must for the simulation Dumb is usable after this point

pub fn prediction(&self) -> Vec<(f64, f64)>[src]

pub fn get_linear_regression(&self) -> LinearRegression[src]

pub fn plot_to_file(&self, filename: String)[src]

Trait Implementations

impl Plotable for Dumb[src]

Auto Trait Implementations

impl RefUnwindSafe for Dumb

impl Send for Dumb

impl Sync for Dumb

impl Unpin for Dumb

impl UnwindSafe for Dumb

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized, [src]

impl<T> Borrow<T> for T where
    T: ?Sized, [src]

impl<T> BorrowMut<T> for T where
    T: ?Sized, [src]

impl<T> From<T> for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, [src]

impl<T, U> TryFrom<U> for T where
    U: Into<T>, [src]

type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, [src]

type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.