Portable PLS / NIRS engine in C++17 with a stable C ABI and thin first-class bindings for Python, R, MATLAB, JavaScript, Android, Go, Rust, Julia, Ruby, .NET, Lua, Nim.
n4m.<role> namespacemethods.nirs4all.org)aom_chain_ridge_pls - strict-chain AOM Ridge-PLSaom_chain_sweep_run - user-defined native AOM chain sweepaom_operator_pls_stack - native AOM operator PLS score stackaom_pls — AOM-PLS (global adaptive operator selection)ridge_active_superblock — n4m.compose.aom_superblock.ridge_active_superblockridge_global — n4m.model_selection.aom_search.ridge_globalridge_mkl_superblock — n4m.compose.aom_superblock.ridge_mkl_superblockridge_superblock — n4m.compose.aom_superblock.ridge_superblockaom_preprocess — AOM (Adaptive Operator Mixture) preprocessing bankaom_ridge_blender - native AOM Ridge OOF simplex blenderaom_ridge_global - strict-linear AOM Ridge global selectoraom_ridge_mkl_superblock - strict-linear AOM Ridge MKL-light superblockaom_ridge_pls_superblock - strict-linear AOM Ridge-PLS superblockaom_ridge_superblock - strict-linear AOM Ridge superblockaom_robust_hpo - native AOM robust-HPO preprocessing screenaom_staged_chain_campaign - staged strict-chain cartesian screen/refitaom_sweep_run - configurable native AOM preprocessing sweepapproximate_press — Approximate PRESS (leave-one-out by hat-matrix)aug_band_mask — Band Maskingaug_band_perturb — Band Perturbation Augmenteraug_batch_effect — Batch Effect Augmenteraug_channel_dropout — Channel Dropoutaug_dead_band — Dead Band Augmenteraug_detector_rolloff — Detector Roll Off Augmenteraug_edge_artifacts — Edge Artifacts Augmenteraug_edge_curve — Edge Curvature Augmenteraug_emsc_distort — E M S C Distortion Augmenteraug_gauss_jitter — Gaussian Jitteraug_gaussian_noise — Gaussian additive-noise augmentationaug_hetero_noise — Heteroscedastic Noise Augmenteraug_instrument_broaden — Instrumental Broadening Augmenteraug_linear_drift — Linear baseline-drift augmentationaug_local_clip — Local Clipaug_local_mixup — Local Mixup Augmenteraug_local_warp — Local Warp Augmenteraug_magnitude_warp — Magnitude Warpaug_mixup — Mixup augmentationaug_moisture — Moisture Augmenteraug_multiplicative_noise — Multiplicative Noiseaug_particle_size — Particle Size Augmenteraug_path_length — Path Length Augmenteraug_poly_drift — Polynomial Baseline Driftaug_random_x_op — Random X Operationaug_rotate_translate — Rotate Translate Augmenteraug_scatter_sim — Scatter Simulation M S Caug_spike_noise — Spike Noiseaug_spline_curve_simplify — Spline Curve Simplification Augmenteraug_spline_smooth — Spline Smoothing Augmenteraug_spline_x_perturb — Spline X Perturbation Augmenteraug_spline_x_simplify — Spline X Simplification Augmenteraug_spline_y_perturb — Spline Y Perturbation Augmenteraug_stray_light — Stray Light Augmenteraug_temperature — Temperature Augmenteraug_truncated_peak — Truncated Peak Augmenteraug_unsharp_mask — Unsharp Maskaug_wavelength_shift — Wavelength Shiftaug_wavelength_stretch — Wavelength Stretchbagging_pls — Bagging PLSbipls_select — biPLS — Backward Interval PLSboosting_pls — Boosting PLSbve_select — BVE — Backward Variable Eliminationcars_select — CARS — Competitive Adaptive Reweighted Samplingcontinuum_regression — Continuum Regression (Stone & Brooks 1990)cppls — Powered PLS (Indahl 2005)di_pls — Domain-Invariant PLS (di-PLS)pls_diagnostics — n4m.metrics.diagnostics.pls_diagnosticsregression_metrics — n4m.metrics.scoring.regression_metricsds — Direct Standardisationecr — ECR — Elastic Component Regressionemcuve_select — EMCUVE — Ensemble MC-UVEfilter_composite — Composite Filterfilter_correlation — Correlation Filterfilter_leverage — High Leverage Filterfilter_quality — Spectral Quality Filterfilter_variance — Variance Filterfilter_x_outlier — X Outlier Filterfilter_y_outlier — Y Outlier Filterfused_sparse_pls — Fused-sparse PLSga_select — GA-PLS — Genetic Algorithm variable selectiongpr_pls — Gaussian Process on PLS scoresgroup_sparse_pls — Group-sparse PLS (Liquet 2016)interval_generator — Interval Generatorinterval_select — iPLS — Interval PLS (moving-window)ipw_select — IPW — Iterative Predictor Weightingirf_select — IRF — Iterative Random Forestiriv_select — IRIV — Iteratively Retaining Informative Variableskernel_pls_rbf — Kernel PLS (Rosipal & Trejo 2001)lw_pls — Locally-Weighted PLS (LW-PLS)mb_pls — Multi-block PLS (Westerhuis 1998)mir_pls — MIR-PLS (Mid-InfraRed PLS, regularised)missing_aware_nipals — Missing-aware NIPALSmoment_stack — OOF stack over native moment headsn_pls — N-way PLS (Trilinear PLS, Bro 1996)o2pls — O2-PLS (two-way orthogonal)on_pls — OnPLS (Orthogonal N-block PLS)one_se_rule — One-SE rule for component selectionopls — Orthogonal PLS (OPLS)pcr — Principal Components Regressionpds — Piecewise Direct Standardisationpls — PLS regression (SIMPLS)pls_cox — PLS-Cox (survival regression)pls_diagnostic_dmodx — DModX (distance to the model in X)pls_diagnostic_q — Q residual (squared prediction error)pls_diagnostic_t2 — Hotelling T² scorepls_glm — PLS-GLM (Generalised Linear Model PLS)pls_lda — PLS-LDApls_logistic — PLS-logistic regressionpls_monitoring — PLS monitoring (T² + Q with control limits)pls_qda — PLS-QDApop_pls — POP-PLS (per-component operator selection)pp_airpls — Air P L Spp_area — Area Normalizationpp_arpls — Ar P L Spp_asls — As L Spp_baseline — Baseline Centerpp_beads — B E A D Spp_cow_align — Correlation Optimized Warpingpp_crop — Crop Transformerpp_derivate — Derivatepp_detrend — De-trendingpp_direct_standardization — Direct Standardizationpp_dtw_align — Dynamic Time Warping Alignmentpp_emsc — Extended Multiplicative Scatter Correction (EMSC)pp_epo — E P Opp_fck_static — F C K Static Transformerpp_first_derivative — First derivativepp_flex_pca — Flexible P C App_flex_svd — Flexible S V Dpp_frac_to_pct — Fraction To Percentpp_from_absorbance — From Absorbancepp_gaussian — Gaussian smoothingpp_haar — Haarpp_iasls — I As L Spp_icoshift_align — Icoshift Alignmentpp_imodpoly — I Mod Polypp_kbins_disc — Integer K Bins Discretizerpp_kubelka_munk — Kubelka Munkpp_local_centering — Local Centeringpp_localized_msc — Localized M S Cpp_log — Log Transformpp_lsnv — L S N Vpp_modpoly — Mod Polypp_msc — Multiplicative Scatter Correction (MSC)pp_normalize — Normalizepp_norris_williams — Norris Williamspp_osc — O S Cpp_pct_to_frac — Percent To Fractionpp_piecewise_direct_standardization — Piecewise Direct Standardizationpp_piecewise_msc — Piecewise M S Cpp_piecewise_snv — Piecewise S N Vpp_range_disc — Range Discretizerpp_resample — Resample Transformerpp_resampler — Resamplerpp_rnv — Robust Normal Variate (RNV)pp_robust_direct_standardization — Robust Direct Standardizationpp_rolling_ball — Rolling Ballpp_saps — Score Augmented Projection Standardizationpp_savgol — Savitzky–Golay smoothing / derivativepp_second_derivative — Second derivativepp_simple_scale — Simple Scalepp_slope_bias — Slope Bias Correctionpp_snip — S N I Ppp_snv — Standard Normal Variate (SNV)pp_to_absorbance — To Absorbancepp_vsn — Variable Sorting Normalizationpp_wavelet — Waveletpp_wavelet_denoise — Wavelet Denoisepp_wavelet_features — Wavelet Featurespp_wavelet_pca — Wavelet P C App_wavelet_svd — Wavelet S V Dpp_weighted_snv — Weighted S N Vpp_xcorr_align — Cross Correlation Alignmentpso_select — PSO-PLS — Particle Swarm Optimisationrandom_frog_select — Random Frograndom_subspace_pls — Random-subspace PLSrandomization_select — Randomisation test (Y-permutation)recursive_pls — Recursive (moving-window) PLSrep_select — REP — Recursive Elimination of Predictorsridge - direct closed-form Ridge regressionridge_pls — Ridge-augmented PLSrobust_pls — Robust PLS (Partial Robust M-regression)rosa — ROSA (Response-Oriented Sequential Alternation)scars_select — SCARS — Stability-CARSshaving_select — Shaving (recursive elimination)sipls_select — siPLS — Synergy Interval PLSso_pls — Sequential and Orthogonalised PLS (SO-PLS)spa_select — SPA — Successive Projections Algorithmsparse_pls_da — Sparse PLS-DA (Lê Cao 2008)sparse_simpls — Sparse SIMPLS (Chun & Keleş 2010)split_binned_strat_group_kfold — Binned Stratified Group K Fold Splittersplit_kbins_stratified — K Bins Stratified Splittersplit_kennard_stone — Kennard Stone Splittersplit_kmeans — K Means Splittersplit_split_splitter — S Plit Splittersplit_spxy — S P X Y Splittersplit_spxy_fold — S P X Y Fold Splittersplit_spxy_g_fold — S P X Y Group Fold Splittersplit_systematic_circular — Systematic Circular Splitterst_select — ST-PLS — Score Threshold selectionstability_select — MC-UVE (Monte-Carlo coefficient stability)t2_select — Hotelling T² loading selectionhotelling_t2 — n4m.outlier_detection.hotelling_t2q_residuals — n4m.outlier_detection.q_residualssignal_type_detector — n4m.transform.signal_conversion.signal_type_detectortransfer_metrics — n4m.domain_adaptation.metrics.transfer_metricsuve_select — UVE — Uninformative Variable Eliminationvariable_select_coef — Coefficient-magnitude selectionvariable_select_sr — Selectivity Ratiovariable_select_vip — VIP (Variable Importance in Projection)vip_spa_select — VIP-seeded SPAvissa_select — VISSA — Variable Iterative Space-Shrinkageweighted_pls — Sample-weighted PLSwvc_select — WVC — Weighted Variable Contributionwvc_threshold_select — WVC-threshold selectionq_residuals — n4m.outlier_detection.q_residuals¶Namespace: n4m.outlier_detection · Fully-qualified: n4m.outlier_detection.q_residuals · Catalog id: utilities.q_residuals
C ABI symbols (ABI 2.0): n4m_outlier_detection_q_residuals
Auto-discovered from source tree in M2. Refine in subsequent phases (fixtures, references, bindings, publications).
See also: methods index.