Enum ErrorModel

pub enum ErrorModel {
    Additive {
        lambda: f64,
        poly: ErrorPoly,
    },
    Proportional {
        gamma: f64,
        poly: ErrorPoly,
    },
}

Model for calculating observation errors in pharmacometric analyses

An ErrorModel defines how the standard deviation of observations is calculated based on the type of error model used and its parameters.

Variants

Additive

Additive error model, where error is independent of concentration

Contains:

• lambda - Lambda parameter for scaling errors
• poly - Error polynomial coefficients (c0, c1, c2, c3)

Fields

lambda: f64

Lambda parameter for scaling errors

poly: ErrorPoly

Error polynomial coefficients (c0, c1, c2, c3)

Proportional

Proportional error model, where error scales with concentration

Contains:

• gamma - Gamma parameter for scaling errors
• poly - Error polynomial coefficients (c0, c1, c2, c3)

Fields

gamma: f64

Gamma parameter for scaling errors

poly: ErrorPoly

Error polynomial coefficients (c0, c1, c2, c3)

Implementations

impl ErrorModel

pub fn additive(poly: ErrorPoly, lambda: f64) -> ErrorModel

Create a new additive error model

Arguments

• poly - Error polynomial coefficients (c0, c1, c2, c3)
• lambda - Lambda parameter for scaling errors

Returns

A new additive error model

pub fn proportional(poly: ErrorPoly, gamma: f64) -> ErrorModel

Create a new proportional error model

Arguments

• poly - Error polynomial coefficients (c0, c1, c2, c3)
• gamma - Gamma parameter for scaling errors

Returns

A new proportional error model

pub fn errorpoly(&self) -> ErrorPoly

Get the error polynomial coefficients

Returns

The error polynomial coefficients (c0, c1, c2, c3)

pub fn set_polynomial(&mut self, poly: ErrorPoly)

Set the error polynomial coefficients

Arguments

• poly - New error polynomial coefficients (c0, c1, c2, c3)

Returns

The updated error model with the new polynomial coefficients

pub fn scalar(&self) -> f64

Get the scaling parameter

pub fn set_scalar(&mut self, scalar: f64)

Set the scaling parameter

pub fn sigma(&self, prediction: &Prediction) -> Result<f64, ErrorModelError>

Estimate the standard deviation for a prediction

Calculates the standard deviation based on the error model type, using either observation-specific error polynomial coefficients or the model’s default coefficients.

Arguments

• prediction - The prediction for which to estimate the standard deviation

Returns

The estimated standard deviation of the prediction

pub fn variance(&self, prediction: &Prediction) -> Result<f64, ErrorModelError>

Estimate the variance of the observation

This is a conveniecen function which calls ErrorModel::sigma, and squares the result.

pub fn sigma_from_value(&self, value: f64) -> Result<f64, ErrorModelError>

Estimate the standard deviation for a raw observation value

Calculates the standard deviation based on the error model type, using the model’s default coefficients and a provided observation value.

Arguments

• value - The observation value for which to estimate the standard deviation

Returns

The estimated standard deviation for the given value

pub fn variance_from_value(&self, value: f64) -> Result<f64, ErrorModelError>

Estimate the variance for a raw observation value

This is a conveniecen function which calls ErrorModel::sigma_from_value, and squares the result.

Trait Implementations

impl Clone for ErrorModel

fn clone(&self) -> ErrorModel

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for ErrorModel

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for ErrorModel

fn deserialize<__D>( __deserializer: __D, ) -> Result<ErrorModel, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl From<Error> for ErrorModel

fn from(error: Error) -> Self

Converts to this type from the input type.

impl Serialize for ErrorModel

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.