Distributions Hermite Polynomial Approximation

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Documentation for package ‘hpa’ version 1.3.3

• DESCRIPTION file.

Help Pages

bspline	B-splines generation, estimation and combination
bsplineComb	B-splines generation, estimation and combination
bsplineEstimate	B-splines generation, estimation and combination
bsplineGenerate	B-splines generation, estimation and combination
coef.hpaBinary	Extract coefficients from hpaBinary object
coef.hpaML	Extract coefficients from hpaML object
coef.hpaSelection	Extract coefficients from hpaSelection object
dhpa	Probabilities and Moments Hermite Polynomial Approximation
dhpa0	Fast pdf and cdf for standardized univariate PGN distribution
dhpaDiff	Probabilities and Moments Hermite Polynomial Approximation
dhsa	Probabilities and Moments Hermite Spline Approximation
dnorm_parallel	Calculate normal pdf in parallel
dtrhpa	Probabilities and Moments Hermite Polynomial Approximation
ehpa	Probabilities and Moments Hermite Polynomial Approximation
ehpaDiff	Probabilities and Moments Hermite Polynomial Approximation
ehsa	Probabilities and Moments Hermite Spline Approximation
etrhpa	Probabilities and Moments Hermite Polynomial Approximation
hpaBinary	Semi-nonparametric single index binary choice model estimation
hpaDist	Probabilities and Moments Hermite Polynomial Approximation
hpaDist0	Fast pdf and cdf for standardized univariate PGN distribution
hpaML	Semi-nonparametric maximum likelihood estimation
hpaSelection	Perform semi-nonparametric selection model estimation
hsaDist	Probabilities and Moments Hermite Spline Approximation
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
phpa0	Fast pdf and cdf for standardized univariate PGN distribution
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
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
qhpa	Probabilities and Moments Hermite Polynomial Approximation
rhpa	Probabilities and Moments Hermite Polynomial Approximation
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
vcov.hpaBinary	Extract covariance matrix from hpaBinary object
vcov.hpaML	Extract covariance matrix from hpaML object
vcov.hpaSelection	Extract covariance matrix from hpaSelection object