Title: Impute and Analyze Data with BLOQ Observations
Description: It includes estimating the area under the concentrations
versus time curve (AUC) and its standard error for data with
Below the Limit of Quantification (BLOQ) observations. Two
approaches are implemented: direct estimation using censored maximum
error using imputed data. Technical details can found in
Barnett, Helen Yvette, Helena Geys, Tom Jacobs, and Thomas Jaki.
"Methods for Non-Compartmental Pharmacokinetic Analysis With Observations
Below the Limit of Quantification." Statistics in Biopharmaceutical

Author: Daniel Brunner (aut), Constantin Weiser (ctr), Andre Romahn (ctr)
Description: Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <DOI:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.
Depends: Rcpp (>= 0.12.7), mvQuad, ucminf, numDeriv, randtoolbox

Imports: Rcpp (>= 0.11.0), mvQuad, numDeriv, randtoolbox, Formula,

Title: Stochastic Rainfall Generator Bartlett-Lewis Rectangular Pulse
Description: Due to a limited availability of observed high-resolution precipitation records with adequate length, simulations with stochastic precipitation models are used to generate series for subsequent studies [e.g. Khaliq and Cunmae, 1996, <doi:10.1016/0022-1694(95)02894-3>, Vandenberghe et al., 2011, <doi:10.1029/2009WR008388>]. This package contains an R implementation of the original Bartlett-Lewis rectangular pulse model (BLRPM), developed by Rodriguez-Iturbe et al. (1987) <doi:10.1098/rspa.1987.0039>. It contains a function for simulating a precipitation time series based on storms and cells generated by the model with given or estimated model parameters. Additionally BLRPM parameters can be estimated from a given or simulated precipitation time series. The model simulations can be plotted in a three-layer plot including an overview of generated storms and cells by the model (which can also be plotted individually), a continuous step-function and a discrete precipitation time series at a chosen aggregation level.