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| dhpa | Probabilities and Moments Hermite Polynomial Approximation |
| dhpaDiff | Probabilities and Moments Hermite Polynomial Approximation |
| dnorm_parallel | Calculate normal pdf in parallel |
| dtrhpa | Probabilities and Moments Hermite Polynomial Approximation |
| ehpa | Probabilities and Moments Hermite Polynomial Approximation |
| etrhpa | Probabilities and Moments Hermite Polynomial Approximation |
| hpaBinary | Semi-nonparametric single index binary choice model estimation |
| hpaDist | Probabilities and Moments Hermite Polynomial Approximation |
| hpaML | Semi-nonparametric maximum likelihood estimation |
| hpaSelection | Perform semi-nonparametric selection model estimation |
| ihpa | Probabilities and Moments Hermite Polynomial Approximation |
| ihpaDiff | Probabilities and Moments Hermite Polynomial Approximation |
| itrhpa | Probabilities and Moments Hermite Polynomial Approximation |
| logLik.hpaBinary | Calculates log-likelihood for "hpaBinary" object |
| logLik.hpaML | Calculates log-likelihood for "hpaML" object |
| logLik.hpaSelection | Calculates log-likelihood for "hpaSelection" object |
| logLik_hpaBinary | Calculates log-likelihood for "hpaBinary" object |
| logLik_hpaML | Calculates log-likelihood for "hpaML" object |
| logLik_hpaSelection | Calculates log-likelihood for "hpaSelection" object |
| mecdf | Calculates multivariate empirical cumulative distribution function |
| normalMoment | Calculate k-th order moment of normal distribution |
| phpa | Probabilities and Moments Hermite Polynomial Approximation |
| plot.hpaBinary | Plot hpaBinary random errors approximated density |
| plot.hpaML | Plot approximated marginal density using hpaML output |
| plot.hpaSelection | Plot hpaSelection random errors approximated density |
| plot_hpaBinary | Plot hpaBinary random errors approximated density |
| plot_hpaSelection | Plot hpaSelection random errors approximated density |
| pnorm_parallel | Calculate normal cdf in parallel |
| polynomialIndex | Multivariate Polynomial Representation |
| predict.hpaBinary | Predict method for hpaBinary |
| predict.hpaML | Predict method for hpaML |
| predict.hpaSelection | Predict outcome and selection equation values from hpaSelection model |
| predict_hpaBinary | Predict method for hpaBinary |
| predict_hpaML | Predict method for hpaML |
| predict_hpaSelection | Predict outcome and selection equation values from hpaSelection model |
| print.hpaBinary | Print method for "hpaBinary" object |
| print.hpaML | Print method for "hpaML" object |
| print.hpaSelection | Print method for "hpaSelection" object |
| print.summary.hpaBinary | Summary for "hpaBinary" object |
| print.summary.hpaML | Summary for hpaML output |
| print.summary.hpaSelection | Summary for "hpaSelection" object |
| printPolynomial | Multivariate Polynomial Representation |
| print_summary_hpaBinary | Summary for hpaBinary output |
| print_summary_hpaML | Summary for hpaML output |
| print_summary_hpaSelection | Summary for hpaSelection output |
| summary.hpaBinary | Summarizing hpaBinary Fits |
| summary.hpaML | Summarizing hpaML Fits |
| summary.hpaSelection | Summarizing hpaSelection Fits |
| summary_hpaBinary | Summarizing hpaBinary Fits |
| summary_hpaML | Summarizing hpaML Fits |
| summary_hpaSelection | Summarizing hpaSelection Fits |
| truncatedNormalMoment | Calculate k-th order moment of truncated normal distribution |