Struct RegressionLayer

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pub struct RegressionLayer {Show 15 fields
    pub method: String,
    pub beta_t: Option<Vec<f64>>,
    pub fitted_values: Vec<f64>,
    pub residuals: Vec<f64>,
    pub observed_y: Vec<f64>,
    pub r_squared: f64,
    pub adj_r_squared: Option<f64>,
    pub intercept: f64,
    pub ncomp: usize,
    pub argvals: Option<Vec<f64>>,
    pub beta_se: Option<Vec<f64>>,
    pub model_name: Option<String>,
    pub n_obs: Option<usize>,
    pub fpca: Option<Box<FpcaLayer>>,
    pub selection_extra: Option<HashMap<String, Vec<f64>>>,
}

Expand description

Scalar-on-function regression fit.

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§method: String

Method name (e.g., “fregre_lm”, “fregre_pls”, “fregre_np”, “elastic”).

§beta_t: Option<Vec<f64>>

Functional coefficient β(t) (length m). None for nonparametric.

§fitted_values: Vec<f64>

Fitted values (length n).

§residuals: Vec<f64>

Residuals (length n).

§observed_y: Vec<f64>

Observed response (length n).

§r_squared: f64

R².

§adj_r_squared: Option<f64>

Adjusted R².

§intercept: f64

Intercept.

§ncomp: usize

Number of components used (0 for nonparametric).

§argvals: Option<Vec<f64>>

Evaluation grid for β(t).

§beta_se: Option<Vec<f64>>

Pointwise standard errors of β(t).

§model_name: Option<String>

Optional: human-readable model name.

§n_obs: Option<usize>

Optional: number of training observations.

§fpca: Option<Box<FpcaLayer>>

Optional: FPCA decomposition used by the model (needed for explain functions).

§selection_extra: Option<HashMap<String, Vec<f64>>>

Optional: model selection details.

Trait Implementations§

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impl Clone for RegressionLayer

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fn clone(&self) -> RegressionLayer

Returns a duplicate of the value. Read more

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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more

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impl Debug for RegressionLayer

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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impl From<&FregreLmResult> for RegressionLayer

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fn from(fit: &FregreLmResult) -> Self

Converts to this type from the input type.

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impl From<&PlsRegressionResult> for RegressionLayer

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fn from(fit: &PlsRegressionResult) -> Self

Converts to this type from the input type.

Auto Trait Implementations§

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impl UnwindSafe for RegressionLayer

Blanket Implementations§

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

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

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impl<T> CloneToUninit for T
where T: Clone,

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unsafe fn clone_to_uninit(&self, dest: *mut u8)

🔬This is a nightly-only experimental API. (clone_to_uninit)

Performs copy-assignment from self to dest. Read more

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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> IntoEither for T

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fn into_either(self, into_left: bool) -> Either<Self, Self>

Converts self into a Left variant of Either<Self, Self> if into_left is true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

Converts self into a Left variant of Either<Self, Self> if into_left(&self) returns true. Converts self into a Right variant of Either<Self, Self> otherwise. Read more

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