| qrnn-package | Quantile Regression Neural Network |
| adam | Adaptive stochastic gradient descent optimization algorithm (Adam) |
| censored.mean | A hybrid mean/median function for left censored variables |
| composite.stack | Reformat data matrices for composite quantile regression |
| dquantile | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| dummy.code | Convert a factor to a matrix of dummy codes |
| elu | Transfer functions and their derivatives |
| elu.prime | Transfer functions and their derivatives |
| gam.style | Modified generalized additive model plots for interpreting QRNN models |
| hramp | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| hramp.prime | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| huber | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| huber.prime | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| linear | Transfer functions and their derivatives |
| linear.prime | Transfer functions and their derivatives |
| lrelu | Transfer functions and their derivatives |
| lrelu.prime | Transfer functions and their derivatives |
| mcqrnn | Monotone composite quantile regression neural network (MCQRNN) for simultaneous estimation of multiple non-crossing quantiles |
| mcqrnn.fit | Monotone composite quantile regression neural network (MCQRNN) for simultaneous estimation of multiple non-crossing quantiles |
| mcqrnn.predict | Monotone composite quantile regression neural network (MCQRNN) for simultaneous estimation of multiple non-crossing quantiles |
| pquantile | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| pquantile.nw | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| qquantile | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| qquantile.nw | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| qrnn | Quantile Regression Neural Network |
| qrnn.cost | Smooth approximation to the tilted absolute value cost function |
| qrnn.fit | Main function used to fit a QRNN model or ensemble of QRNN models |
| qrnn.initialize | Initialize a QRNN weight vector |
| qrnn.predict | Evaluate quantiles from trained QRNN model |
| qrnn.rbf | Radial basis function kernel |
| qrnn2.fit | Fit and make predictions from QRNN models with two hidden layers |
| qrnn2.predict | Fit and make predictions from QRNN models with two hidden layers |
| relu | Transfer functions and their derivatives |
| relu.prime | Transfer functions and their derivatives |
| rquantile | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| rquantile.nw | Interpolated quantile distribution with exponential tails and Nadaraya-Watson quantile distribution |
| sigmoid | Transfer functions and their derivatives |
| sigmoid.prime | Transfer functions and their derivatives |
| softmax | Transfer functions and their derivatives |
| softplus | Transfer functions and their derivatives |
| softplus.prime | Transfer functions and their derivatives |
| tilted.abs | Tilted absolute value function |
| tilted.approx | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| tilted.approx.prime | Huber norm and Huber approximations to the ramp and tilted absolute value functions |
| YVRprecip | Daily precipitation data at Vancouver Int'l Airport (YVR) |