Hydrologic indices for daily time series data

Hydrologic Indices for Daily Time Series Data

Hydrological Tools for Handling Hydro-Meteorological Data
Records
Read, plot, manipulate and process hydro-meteorological data records (with special features for Argentina and Chile data-sets).
ggplot2, plotly, lubridate, utils, methods, readxl, reshape2,
magrittr, Rcpp

ggplot2, plotly, lubridate, utils, methods, readxl, reshape2,
magrittr, tibble, zoo, Rcpp

Focuses on data processing and visualization in hydrology and
climate forecasting. Main function includes data extraction, data downscaling, data
resampling, gap filler of precipitation, bias correction of forecasting data, flexible
time series plot, and spatial map generation. It is a good pre-processing and
post-processing tool for hydrological and hydraulic modellers.

Focuses on data processing and visualization in hydrology and
climate forecasting. Main function includes data extraction, data downscaling,
data resampling, gap filler of precipitation, bias correction of forecasting
data, flexible time series plot, and spatial map generation. It is a good pre-
processing and post-processing tool for hydrological and hydraulic modellers.

Generic N-Dimensional Hyperplane Fitting with Heteroscedastic
Covariant Errors and Intrinsic Scatter
Includes two main high level codes for hyperplane fitting (hyper.fit) and visualising (hyper.plot2d / hyper.plot3d). In simple terms this allows the user to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimension dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane.
R (>= 3.00), magicaxis, MASS, rgl, LaplacesDemon

A suite of routines for the hyperdirichlet distribution; supersedes the hyperdirichlet package for most purposes.

A suite of routines for the hyperdirichlet distribution; supersedes the 'hyperdirichlet' package for most purposes.