Package index • curveRcore

Forward Models

Five canonical sigmoid/saturation model functions.

available_models(): List all available model names
model_params(): Model registry: parameter names for each model family
build_nls_formulas(): Build NLS Formulas for Candidate Models
gompertz4(): Four-Parameter Gompertz Forward Function
logistic4(): Four-Parameter Logistic (4PL) Forward Function
logistic5(): Five-Parameter Logistic (5PL) Forward Function
loglogistic4(): Four-Parameter Log-Logistic (Dose-Response) Forward Function
loglogistic5(): Five-Parameter Generalised Logistic (Richards) Forward Function
adaptive_constraint_profile(): Build an Adaptive Constraint Profile from Observed Data
validate_fixed_lower_asymptote(): Validate a Fixed Lower Asymptote Before Log Transformation

Constructor functions for fit settings objects.

new_antigen_constraints(): Create Antigen-Level Constraint Settings
new_calibration_result(): Construct a Calibration Result Object
new_calibration_result_multiplate(): Construct a Multi-Plate Calibration Result
new_fit_options(): Create Model Fitting and Grid Options
new_study_params(): Create Study-Level Fitting Parameters
resolve_effective_models(): Resolve Effective Models for a Given Configuration
resolve_fixed_lower_asymptote(): Resolve the Fixed Lower Asymptote Value
resolve_response_col(): Resolve the Response Column Name

The shared calibration_result S3 class.

agreement_metrics(): Compute Agreement Metrics Between Paired Predictions
compare_calibrations(): Compare Two Calibration Results (Grid Predictions)
compare_parameters(): Compare Parameters Between Two Calibration Results
compare_samples(): Compare Sample Predictions Between Two Calibration Results
new_calibration_result(): Construct a Calibration Result Object
new_calibration_result_multiplate(): Construct a Multi-Plate Calibration Result

Broom-style helpers for extracting tabular data.

pcov_from_se() se_from_pcov(): Convert between posterior CV (pcov) and the log10-scale concentration SD
tidy_grid(): Tidy the precision grid from a calibration result
tidy_samples(): Tidy the per-sample predictions from a calibration result

Model gating and best-model selection.

LOD, MDC, RDL, and shape-LOQ functions.

compute_detection_limits(): Compute and attach detection limits to a calibration_result
compute_detection_limits_multiplate(): Compute detection limits for all plates in a multiplate result
compute_shape_loq_from_grid(): Compute curvature-based (shape) LOQs from an enriched grid
.empty_detection_limits(): Empty detection_limits list for non-converged models
enrich_grid_with_d2y(): Add a d2y_dx2 column to an existing prediction grid

Prediction grid generation and curve confidence intervals.

Data transforms applied before fitting.

preprocess_standards(): Full Preprocessing Pipeline for Standard Curve Data
perform_blank_operation(): Apply a Blank Operation to Standard Curve Data
compute_concentration(): Compute Concentration from Dilution and Undiluted Standard
compute_log_response(): Log10-Transform the Assay Response
correct_prozone(): Correct the Prozone (Hook) Effect

Back-calculation functions for all five models.

inv_gompertz4() inv_gompertz4_fixed(): Inverse of the Gompertz Model
inv_logistic4() inv_logistic4_fixed(): Inverse of the 4PL Model
inv_logistic5() inv_logistic5_fixed(): Inverse of the 5PL Model
inv_loglogistic4() inv_loglogistic4_fixed(): Inverse of the loglogistic4 Model
inv_loglogistic5() inv_loglogistic5_fixed(): Inverse of the loglogistic5 Model

Analytical derivatives and gradient vectors.

dydx_gompertz4(): First Derivative of the Gompertz Model
dydx_logistic4(): First Derivative of the 4PL Model
dydx_logistic5(): First Derivative of the 5PL Model
dydx_loglogistic4(): First Derivative of the loglogistic4 Model
dydx_loglogistic5(): First Derivative of the loglogistic5 Model
d2x_gompertz4(): Second Derivative of the Gompertz Model
d2x_logistic4(): Second Derivative of the 4PL Model
d2x_logistic5(): Second Derivative of the 5PL Model (Numerical)
d2x_loglogistic4(): Second Derivative of the loglogistic4 Model (Numerical)
d2x_loglogistic5(): Second Derivative of the loglogistic5 Model (Numerical)
grad_gompertz4(): Analytical Gradient of the Inverse Gompertz
grad_logistic4(): Analytical Gradient of the Inverse 4PL
grad_logistic5(): Analytical Gradient of the Inverse 5PL
grad_loglogistic4(): Analytical Gradient of the Inverse loglogistic4
grad_loglogistic5(): Analytical Gradient of the Inverse loglogistic5
make_inv_and_grad_fixed(): Build Inverse, Gradient, and grad_y Closures for a Model

Data from immune assays

Internal helpers and shared utilities.

filter_by_curve_id(): Filter a Dataset List by Curve ID
safe_unique(): Safe unique with NA handling
geom_mean(): Geometric mean
.extract_param_ci(): Extract parameter CIs from an ensemble entry
.fmt_na(): Format a number for messages, NA-safe
.interp_response(): Linear interpolation of predicted_response at a log10 concentration
.parabolic_refine(): 3-point parabolic interpolation for a set of extremum indices
.safe_invert_model(): Safely invert a named model at a response value
.safe_pow10(): Safe 10^x, NA-propagating