| geosmooth-package | geosmooth package |
| apply.metric.graph.lowpass.path | Apply a Metric Graph Low-Pass Filter Path |
| as.data.frame.synthetic_dataset | Summarize a synthetic dataset as one metadata row |
| assess.gaussian.trend.filtering | Test Constancy and Assess Gaussian Trend-Filtering Prediction |
| assess.logistic.trend.filtering | Test Constancy and Assess Logistic Trend-Filtering Prediction |
| bootstrap.malps | Bootstrap Uncertainty For A Fixed-Selection MALPS Fit |
| compare.masked.graph.fields | Compare Masked Graph Fields with Independent Graph Workers |
| compare.synthetic.dataset | Compare two synthetic datasets scientifically |
| cv.masked.graph.field | Participant-Grouped Nested Cross-Validation for a Masked Graph Field |
| fit.chart.kernel | Fit a Chart-Kernel Smoother |
| fit.density | Fit a Density Estimator |
| fit.gaussian.trend.filtering | Fit Order-2 Gaussian Trend Filtering |
| fit.graph.trend.filtering | Fit Graph Trend Filtering |
| fit.local.likelihood | Fit a Local-Likelihood Density or Bernoulli Smoother |
| fit.logistic.trend.filtering | Fit Order-2 Logistic Trend Filtering |
| fit.lpl.tf | Fit A Local Polynomial Lifting Trend Filter |
| fit.lps | Fit a Local Polynomial Smoother |
| fit.malps | Fit Model-Averaged Local Polynomial Smoothing |
| fit.masked.graph.field | Fit a Graph Field from Partially Observed Responses |
| fit.metric.graph.lowpass | Fit Metric-Conductance Graph Low-Pass Regression |
| fit.neighbor.probability | Nearest-Person and Nearest-Case Binary Probability Estimators |
| fit.ps.lps | Fit Prediction-Synchronized Local Polynomial Smoothing |
| fit.pttf.trend.filtering | Fit A Parallel-Transport Trend Filter From A PTTF Operator |
| fit.slpl.tf | Fit A Fixed-Operator Synchronized LPL-TF Model |
| fit.ssrhe.hessian.l1.regression | Fit SSRHE-Style Hessian L1 Regression |
| fit.ssrhe.hessian.regression | Fit SSRHE-Style Hessian-Energy Regression |
| fit.ssrhe.hessian.regression.cv | Fit SSRHE-Style Hessian-Energy Regression |
| fit.ssrhe.hessian.regression.gcv | Fit SSRHE-Style Hessian-Energy Regression |
| fit.subject.od | Fit Subject-Occupation Density |
| fitted.chart_kernel | Extract Stored Fitted Values and Response Residuals |
| fitted.gaussian.trend.filtering.fit | Predict from Gaussian Trend Filtering |
| fitted.graph.trend.filtering.fit | Extract Stored Fitted Values and Response Residuals |
| fitted.harmonic_smoother | Extract Stored Fitted Values and Response Residuals |
| fitted.local_likelihood | Extract Stored Fitted Values and Response Residuals |
| fitted.logistic.trend.filtering.fit | Predict from Logistic Trend Filtering |
| fitted.lpl_tf | Extract Stored Fitted Values and Response Residuals |
| fitted.lps | Extract Stored Fitted Values and Response Residuals |
| fitted.malps | Extract Stored Fitted Values and Response Residuals |
| fitted.metric.graph.lowpass.fit | Extract Stored Fitted Values and Response Residuals |
| fitted.metric.graph.lowpass.refit | Extract Stored Fitted Values and Response Residuals |
| fitted.ps_lps | Extract Stored Fitted Values and Response Residuals |
| fitted.pttf.trend.filtering.fit | Extract Stored Fitted Values and Response Residuals |
| fitted.slpl_tf | Extract Stored Fitted Values and Response Residuals |
| fitted.ssrhe.hessian.fit | Extract Stored Fitted Values and Response Residuals |
| fitted.ssrhe.hessian.l1.fit | Extract Stored Fitted Values and Response Residuals |
| fitted.ssrhe.hessian.refit | Extract Stored Fitted Values and Response Residuals |
| geosmooth | geosmooth package |
| get.region.boundary | Get Boundary Vertices of a Region in a Graph |
| graph.trend.filtering.operator | Construct a Graph Trend-Filtering Operator |
| harmonic.smoother | Perform Harmonic Smoothing with Topology Tracking |
| lpl.tf.operator | Construct a Local Polynomial Lifting Trend-Filtering Operator |
| lps.backend.diagnostics | Report LPS Backend and Chart-Dimension Diagnostics |
| lps.grouped.foldid | Build a Cluster-Respecting Fold Assignment |
| lps.nested.cv | Nested Cross-Validation for LPS with Explicit, Recorded Folds |
| lps.pointwise.band | Pointwise Variance and Confidence Band for a Fixed-Configuration LPS Fit |
| lps.smoother.matrix | Extract the Linear-Smoother Matrix of a Fixed-Configuration LPS Fit |
| malps.gcv | Compute MALPS Linear-Smoother Diagnostics |
| malps.smoother.matrix | Construct The Conditional MALPS Smoother Matrix |
| materialize.synthetic | Materialize a synthetic-data specification |
| materialize.synthetic.instance | Materialize a frozen synthetic instance |
| metric.graph.heat.eta.grid | Construct a Graph Heat-Time Grid |
| metric.graph.heat.extend.lower | Propose a Guarded Lower Graph Heat Time |
| metric.graph.lowpass.basis | Construct a Reusable Metric Graph Low-Pass Spectral Basis |
| metric.graph.lowpass.operator | Construct a Metric-Conductance Graph Low-Pass Operator |
| model-summary | Summarize a Geometric Smoother or Probability-Mass Fit |
| model-values | Extract Stored Fitted Values and Response Residuals |
| normalize.density | Normalize Fitted Values Into a Density |
| normalize.density.default | Normalize Fitted Values Into a Density |
| normalize.density.lps | Normalize Fitted Values Into a Density |
| normalize.density.metric.graph.lowpass.fit | Normalize Fitted Values Into a Density |
| normalize.density.metric.graph.lowpass.refit | Normalize Fitted Values Into a Density |
| normalize.density.numeric | Normalize Fitted Values Into a Density |
| normalize.density.ps_lps | Normalize Fitted Values Into a Density |
| perform.harmonic.smoothing | Perform Harmonic Smoothing on Graph Function Values |
| plot.harmonic_smoother | Plot Method for Harmonic Smoother Results |
| plot.synthetic_dataset | Plot a canonical synthetic dataset |
| predict.gaussian.trend.filtering.fit | Predict from Gaussian Trend Filtering |
| predict.logistic.trend.filtering.fit | Predict from Logistic Trend Filtering |
| predict.lpl_tf | Predict From A Local Polynomial Lifting Trend Filter |
| predict.lps | Predict from an LPS Fit |
| predict.malps | Predict From A MALPS Fit |
| predict.neighbor.probability.fit | Predict Nearest-Person Binary Probabilities |
| predict.slpl_tf | Predict From A Fixed-Operator Synchronized LPL-TF Model |
| print.chart_kernel | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.density_fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.gaussian.trend.filtering.assessment | Test Constancy and Assess Gaussian Trend-Filtering Prediction |
| print.gaussian.trend.filtering.fit | Predict from Gaussian Trend Filtering |
| print.graph.trend.filtering.fit | Print Geosmooth S3 Objects |
| print.harmonic_smoother | Print Method for Harmonic Smoother Results |
| print.local_likelihood | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.logistic.trend.filtering.assessment | Test Constancy and Assess Logistic Trend-Filtering Prediction |
| print.logistic.trend.filtering.fit | Predict from Logistic Trend Filtering |
| print.lpl_tf | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.lpl_tf_operator | Print Geosmooth S3 Objects |
| print.lps | Print Geosmooth S3 Objects |
| print.malps | Print Geosmooth S3 Objects |
| print.malps_bootstrap | Print Geosmooth S3 Objects |
| print.metric.graph.lowpass.fit | Print Geosmooth S3 Objects |
| print.metric.graph.lowpass.refit | Print Geosmooth S3 Objects |
| print.ps_lps | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.pttf.trend.filtering.fit | Print Geosmooth S3 Objects |
| print.pttf_operator | Print Geosmooth S3 Objects |
| print.slpl_tf | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.slpl_tf_operator | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.cv.fit | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.fit | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.gcv.fit | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.l1.fit | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.operator | Print Geosmooth S3 Objects |
| print.ssrhe.hessian.refit | Print Geosmooth S3 Objects |
| print.summary.geosmooth_fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| print.summary.harmonic_smoother | Print Method for Summary of Harmonic Smoother Results |
| print.synthetic_dataset | Print a canonical synthetic dataset |
| print.transported.graph.hessian.operator | Print Geosmooth S3 Objects |
| pttf.geometry | Construct PTTF Local Geometry |
| pttf.operator | Construct PTTF Transported-Difference Operators |
| pttf.operator.filter.rows | Filter Rows Of A PTTF Operator |
| refit | Refit A Model Using Its Stored Geometry |
| refit.default | Refit A Model Using Its Stored Geometry |
| refit.lpl.tf | Refit A Local Polynomial Lifting Trend Filter |
| refit.lpl_tf | Refit A Local Polynomial Lifting Trend Filter |
| refit.malps | Refit A MALPS Smoother With A New Response |
| refit.metric.graph.lowpass | Refit Metric-Conductance Graph Low-Pass Regression |
| refit.metric.graph.lowpass.fit | Refit Metric-Conductance Graph Low-Pass Regression |
| refit.slpl.tf | Refit A Fixed-Operator Synchronized LPL-TF Model |
| refit.slpl_tf | Refit A Fixed-Operator Synchronized LPL-TF Model |
| refit.ssrhe.hessian.fit | Refit SSRHE-Style Hessian-Energy Regression |
| refit.ssrhe.hessian.l1.fit | Refit SSRHE-Style Hessian L1 Regression |
| refit.ssrhe.hessian.l1.regression | Refit SSRHE-Style Hessian L1 Regression |
| refit.ssrhe.hessian.regression | Refit SSRHE-Style Hessian-Energy Regression |
| residuals.chart_kernel | Extract Stored Fitted Values and Response Residuals |
| residuals.gaussian.trend.filtering.fit | Predict from Gaussian Trend Filtering |
| residuals.graph.trend.filtering.fit | Extract Stored Fitted Values and Response Residuals |
| residuals.local_likelihood | Extract Stored Fitted Values and Response Residuals |
| residuals.logistic.trend.filtering.fit | Predict from Logistic Trend Filtering |
| residuals.lpl_tf | Extract Stored Fitted Values and Response Residuals |
| residuals.lps | Extract Stored Fitted Values and Response Residuals |
| residuals.malps | Extract Stored Fitted Values and Response Residuals |
| residuals.metric.graph.lowpass.fit | Extract Stored Fitted Values and Response Residuals |
| residuals.metric.graph.lowpass.refit | Extract Stored Fitted Values and Response Residuals |
| residuals.ps_lps | Extract Stored Fitted Values and Response Residuals |
| residuals.pttf.trend.filtering.fit | Extract Stored Fitted Values and Response Residuals |
| residuals.slpl_tf | Extract Stored Fitted Values and Response Residuals |
| residuals.ssrhe.hessian.fit | Extract Stored Fitted Values and Response Residuals |
| residuals.ssrhe.hessian.l1.fit | Extract Stored Fitted Values and Response Residuals |
| residuals.ssrhe.hessian.refit | Extract Stored Fitted Values and Response Residuals |
| select.masked.graph.field | Evaluate Nested Selection Among Candidate Graphs |
| slpl.tf.operator | Construct A Synchronized LPL-TF Fixed Operator |
| smoother.matrix | Extract A Conditional Smoother Matrix |
| smoother.matrix.default | Extract A Conditional Smoother Matrix |
| smoother.matrix.lps | Extract the Linear-Smoother Matrix of a Fixed-Configuration LPS Fit |
| smoother.matrix.malps | Construct The Conditional MALPS Smoother Matrix |
| ssrhe.hessian.operator | Construct an SSRHE-Style Local Hessian Energy Operator |
| ssrhe.support.grid | Build Candidate Support Profiles for SSRHE Adaptive-Radius Tuning |
| summary.chart_kernel | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.density_fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.graph.trend.filtering.fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.harmonic_smoother | Summary Method for Harmonic Smoother Results |
| summary.local_likelihood | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.lpl_tf | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.lps | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.malps | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.metric.graph.lowpass.fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.metric.graph.lowpass.refit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.ps_lps | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.pttf.trend.filtering.fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.slpl_tf | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.ssrhe.hessian.fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.ssrhe.hessian.l1.fit | Summarize a Geometric Smoother or Probability-Mass Fit |
| summary.ssrhe.hessian.refit | Summarize a Geometric Smoother or Probability-Mass Fit |
| support.masked.graph.field | Summarize Measurement Support for a Graph Field |
| synthetic.dataset.checksum | Compute the canonical content checksum of a synthetic dataset |
| synthetic.registry.ids | List maintained synthetic recipe IDs |
| synthetic.registry.seed | Resolve the legacy seed for an SSRHE registry recipe |
| synthetic.registry.spec | Resolve a maintained synthetic recipe |
| synthetic.response.bernoulli | Bernoulli response specification |
| synthetic.response.clustered.gaussian | Clustered Gaussian response specification |
| synthetic.response.gaussian | Gaussian response specification |
| synthetic.response.heteroskedastic.gaussian | Heteroskedastic Gaussian response specification |
| synthetic.response.laplace.outlier | Laplace response with Gaussian contamination |
| synthetic.sampling.stratified | Legacy G4 stratified sampling specification |
| synthetic.spec | Assemble a synthetic-data specification |
| synthetic.truth.gaussian.mixture | Specify a Gaussian-mixture truth |
| synthetic.truth.logit | Specify a sinusoidal finite-design logit truth |
| synthetic.truth.named | Specify a versioned named truth evaluator |
| synthetic.truth.occupation.mixture | Specify a finite-design occupation-mixture truth |
| synthetic.truth.polynomial | Specify a polynomial truth |
| transported.graph.hessian.operator | Construct a Transported Graph Hessian Operator |
| unfold.simplex.chart | Unfold a Local Neighborhood of the L-infinity Simplex |
| validate.synthetic.dataset | Validate a canonical synthetic dataset |