Struct SubjectPredictions 

pub struct SubjectPredictions { /* private fields */ }

Container for predictions associated with a single subject.

This struct holds all predictions for a subject along with methods for calculating aggregate likelihood and error metrics.

Implementations

impl SubjectPredictions

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

Calculate the log-likelihood of all predictions given an error model.

This sums the log-likelihood of each prediction to get the joint log-likelihood. This is numerically stable and avoids underflow issues that can occur when computing products of small probabilities.

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 calculating the likelihood

Returns

The sum of all individual prediction log-likelihoods. Returns 0.0 for empty prediction sets (log of 1.0).

Example

let log_lik = subject_predictions.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 all predictions.

Deprecated: Use log_likelihood instead for better numerical stability. This method exponentiates the log-likelihood.

Parameters

• error_models: The error models to use for calculating the likelihood

Returns

The product of all individual prediction likelihoods. Returns 1.0 for empty prediction sets.

pub fn add_prediction(&mut self, prediction: Prediction)

Add a new prediction to the collection.

Parameters

• prediction: The prediction to add

pub fn predictions(&self) -> &Vec<Prediction>

Get a reference to the vector of predictions.

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

Return a flat vector of prediction values.

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

Return a flat vector of time points.

pub fn flat_observations(&self) -> Vec<Option<f64>>

Return a flat vector of observations.

Trait Implementations

impl Clone for SubjectPredictions

fn clone(&self) -> SubjectPredictions

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SubjectPredictions

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

Formats the value using the given formatter.

impl Default for SubjectPredictions

fn default() -> SubjectPredictions

Returns the “default value” for a type.

impl From<Vec<Prediction>> for SubjectPredictions

fn from(predictions: Vec<Prediction>) -> SubjectPredictions

Converts to this type from the input type.

impl Predictions for SubjectPredictions

fn squared_error(&self) -> f64

Calculate the sum of squared errors for all predictions.

fn get_predictions(&self) -> Vec<Prediction>

Get all predictions as a vector.

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

Calculate the log-likelihood of the predictions given an error model.

fn new(_nparticles: usize) -> Self

Create a new prediction container with specified capacity.