Fast and Stable Fitting of Generalized Linear Models using
'RcppEigen'
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Documentation for package ‘fastglm’ version 0.1.3
Help Pages
| %*%-method | big.matrix prod |
| as.data.frame.fastglm_diagnostics | Display and extract numerical diagnostics |
| as.data.frame.fastglm_prediction | Display and extract predictions with standard errors |
| as.data.frame.fastglm_test | Display and extract hypothesis tests |
| as.data.frame.fastglm_test_list | Display and extract hypothesis tests |
| augment.fastglm_ordinal | Tidy summaries of ordinal fits |
| bread.fastglm | Empirical estimating-function and bread methods for 'fastglm' objects |
| bread.fastglmFit | Empirical estimating-function and bread methods for 'fastglm' objects |
| coef.fastglm_ordinal | Methods for cumulative-link ordinal fits |
| coef.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| confint.fastglm | Confidence intervals for GLM coefficients |
| confint.fastglm_ordinal | Methods for cumulative-link ordinal fits |
| confint.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| estfun.fastglm | Empirical estimating-function and bread methods for 'fastglm' objects |
| estfun.fastglmFit | Empirical estimating-function and bread methods for 'fastglm' objects |
| fastglm | Fast generalized linear model fitting |
| fastglm-confint-methods | Display profile confidence intervals |
| fastglm-diagnostics-methods | Display and extract numerical diagnostics |
| fastglm-prediction-methods | Display and extract predictions with standard errors |
| fastglm-sandwich | Empirical estimating-function and bread methods for 'fastglm' objects |
| fastglm-test-methods | Display and extract hypothesis tests |
| fastglm-tidy | Tidy summaries for fastglm models |
| fastglm.default | Fast generalized linear model fitting |
| fastglm.formula | Fit a generalized linear model from a formula |
| fastglmPure | Fast generalized linear model fitting |
| fastglm_average | Average predictions and contrasts with delta-method uncertainty |
| fastglm_batch | Fit multiple responses using a prepared design |
| fastglm_bootstrap | Refit bootstrap uncertainty for GLMs, count models, and ordinal models |
| fastglm_confint_theta | Profile-likelihood interval for negative-binomial size |
| fastglm_control | Fast generalized linear model fitting |
| fastglm_diagnostics | Numerical diagnostics for a fitted GLM |
| fastglm_fit | Fast generalized linear model fitting |
| fastglm_hurdle | Hurdle (two-part) Poisson / Negative-Binomial regression |
| fastglm_marginal_effects | Average marginal effects for ordinal probabilities |
| fastglm_nb | Fit a negative-binomial GLM with simultaneous (beta, theta) MLE |
| fastglm_ordinal | Fit a cumulative-link model for ordered outcomes |
| fastglm_ordinal.default | Fit a cumulative-link model for ordered outcomes |
| fastglm_ordinal.fastglm_ordinal_design | Fit a cumulative-link model for ordered outcomes |
| fastglm_ordinal.formula | Fit a cumulative-link model for ordered outcomes |
| fastglm_ordinal_assess | Assess ordinal prediction and the common-slope assumption |
| fastglm_ordinal_batch | Fit several ordinal responses using shared predictors |
| fastglm_ordinal_prepare | Prepare predictors for repeated ordinal fits |
| fastglm_ordinal_streaming | Fit an ordinal model from repeatable blocks of observations |
| fastglm_po_test | Test common slopes in a cumulative-link model |
| fastglm_prepare | Prepare a reusable design for repeated GLM fits |
| fastglm_profile_test | Profile likelihood inference |
| fastglm_score_test | Score tests for ordinal model terms and coefficient contrasts |
| fastglm_source | Read a large dataset in repeatable blocks of rows |
| fastglm_source_arrow | Create a source from Parquet partitions |
| fastglm_source_dbi | Create a source from indexed database queries |
| fastglm_streaming | Fit a GLM by reading blocks of observations as needed |
| fastglm_truncated | Zero-truncated count regression |
| fastglm_twopart | Two-part regression for nonnegative continuous outcomes |
| fastglm_vcov | Robust covariance with bounded design memory |
| fastglm_wald_test | Joint Wald tests for model terms and coefficient contrasts |
| fastglm_zi | Zero-inflated Poisson / Negative-Binomial regression |
| glance.fastglm | Tidy summaries for fastglm models |
| glance.fastglmFit | Tidy summaries for fastglm models |
| glance.fastglm_ordinal | Tidy summaries of ordinal fits |
| negbin | Negative binomial family with known dispersion |
| ordinal-partial-methods | Methods for ordinal models with threshold-specific slopes |
| plot.fastglm_ordinal_assessment | Assess ordinal prediction and the common-slope assumption |
| predict.fastglm | Obtains predictions and optionally estimates standard errors of those predictions from a fitted generalized linear model object. |
| predict.fastglm_hurdle | Predictions and inference for two-component models |
| predict.fastglm_ordinal | Predict ordinal probabilities or outcome categories |
| predict.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| predict.fastglm_ordinal_stream | Predictions and residuals from an ordinal source fit |
| predict.fastglm_stream | Stream predictions or diagnostics to a callback |
| predict.fastglm_zi | Predictions and inference for two-component models |
| print.fastglm_bootstrap | Refit bootstrap uncertainty for GLMs, count models, and ordinal models |
| print.fastglm_confint | Display profile confidence intervals |
| print.fastglm_diagnostics | Display and extract numerical diagnostics |
| print.fastglm_ordinal_assessment | Assess ordinal prediction and the common-slope assumption |
| print.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| print.fastglm_prediction | Display and extract predictions with standard errors |
| print.fastglm_test | Display and extract hypothesis tests |
| print.fastglm_test_list | Display and extract hypothesis tests |
| print.summary.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| residuals.fastglm_ordinal | Probability-based residuals for ordinal models |
| residuals.fastglm_ordinal_stream | Predictions and residuals from an ordinal source fit |
| simulate.fastglm_ordinal | Simulate categorical responses from an ordinal fit |
| summary.fastglm | 'summary()' method for 'fastglm' fitted objects |
| summary.fastglmFit | Fast generalized linear model fitting |
| summary.fastglm_ordinal | Methods for cumulative-link ordinal fits |
| summary.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| tidy.fastglm | Tidy summaries for fastglm models |
| tidy.fastglmFit | Tidy summaries for fastglm models |
| tidy.fastglm_ordinal | Tidy summaries of ordinal fits |
| tidy.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| tidy.fastglm_test | Display and extract hypothesis tests |
| tidy.fastglm_test_list | Display and extract hypothesis tests |
| update.fastglm_ordinal | Methods for cumulative-link ordinal fits |
| vcov.fastglm | 'vcov()' method for 'fastglm' fitted objects |
| vcov.fastglmFit | Fast generalized linear model fitting |
| vcov.fastglm_ordinal | Methods for cumulative-link ordinal fits |
| vcov.fastglm_ordinal_partial | Methods for ordinal models with threshold-specific slopes |
| vcovHC.fastglm | Heteroskedasticity-consistent (HC) variance estimators for 'fastglm' objects |
| vcovHC.fastglmFit | Heteroskedasticity-consistent (HC) variance estimators for 'fastglm' objects |