Struct Prediction 

pub struct Prediction { /* private fields */ }

Prediction holds an observation and its prediction at a single time point.

This struct contains all information needed to calculate the likelihood contribution of a single observation.

Implementations

impl Prediction

pub fn time(&self) -> f64

Get the time point of this prediction.

pub fn observation(&self) -> Option<f64>

Get the observed value.

pub fn prediction(&self) -> f64

Get the predicted value.

pub fn outeq(&self) -> usize

Get the output equation index.

pub fn errorpoly(&self) -> Option<ErrorPoly>

Get the error polynomial coefficients, if available.

pub fn prediction_error(&self) -> Option<f64>

Calculate the raw prediction error (prediction - observation).

pub fn percentage_error(&self) -> Option<f64>

Calculate the percentage error as (prediction - observation)/observation * 100.

pub fn absolute_error(&self) -> Option<f64>

Calculate the absolute error |prediction - observation|.

pub fn squared_error(&self) -> Option<f64>

Calculate the squared error (prediction - observation)².

pub fn log_likelihood( &self, error_models: &AssayErrorModels, ) -> Result<f64, PharmsolError>

Calculate the log-likelihood of this prediction given an error model.

This method is numerically stable and handles:

• Regular observations: uses log-normal PDF
• BLOQ (below limit of quantification): uses log-CDF
• ALOQ (above limit of quantification): uses log-survival function

Error Model

Uses observation-based sigma from AssayErrorModels, which is appropriate for non-parametric algorithms (NPAG, NPOD). For parametric algorithms (SAEM, FOCE), use crate::ResidualErrorModels directly.

Parameters

• error_models: The error models to use for sigma calculation

Returns

The log-likelihood value, zero in the case of a missing observation or an error if the likelihood is non-finite.

Example

let log_lik = prediction.log_likelihood(&error_models)?;

pub fn likelihood( &self, error_models: &AssayErrorModels, ) -> Result<f64, PharmsolError>

👎Deprecated since 0.23.0: Use log_likelihood() instead for better numerical stability

Calculate the likelihood of this prediction.

Deprecated: Use log_likelihood instead for better numerical stability. This method is provided for backward compatibility and simply exponentiates the log-likelihood.

Parameters

• error_models: The error models to use for sigma calculation

Returns

The likelihood value (exp of log-likelihood)

pub fn state(&self) -> &Vec<f64>

Get the state vector at this prediction point

pub fn occasion(&self) -> usize

Get the occasion index

pub fn mut_occasion(&mut self) -> &mut usize

Get a mutable reference to the occasion index

pub fn censoring(&self) -> Censor

Get the censoring status

pub fn to_observation(&self) -> Observation

Create an Observation from this prediction

Trait Implementations

impl Clone for Prediction

fn clone(&self) -> Prediction

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Prediction

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

Formats the value using the given formatter.

impl Default for Prediction

fn default() -> Prediction

Returns the “default value” for a type.

impl Display for Prediction

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

Formats the value using the given formatter.