Imports: stringi (>= 1.2), stringr (>= 1.3.1), tibble(>= 1.4.2), pingr

translate and download them into tidy dataframes.
Imports: stringi (>= 1.4), stringr (>= 1.4), tibble(>= 2.1), pingr (>=
Suggests: ggplot2 (>= 3.1), knitr (>= 1.20), rmarkdown (>= 1.10),

Suggests: ggplot2 (>= 3.0), knitr (>= 1.28), rmarkdown (>= 2.1),

Imports: stringi (>= 1.5), stringr (>= 1.4), tibble(>= 3.1), pingr (>=
Suggests: ggplot2 (>= 3.3), knitr (>= 1.31), rmarkdown (>= 2.7),

Title: Hydrologic indices for daily time series data.
Description: Calculates a suite of hydrologic indices for daily time series data that are widely used in hydrology and stream ecology.

Title: Hydrologic indices for daily time series data

Title: Hydrologic Indices for Daily Time Series Data

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

Title: Hydrology and Climate Forecasting
Description: 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.

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.

Title: Generic N-Dimensional Hyperplane Fitting with Heteroscedastic
Author: Aaron Robotham and Danail Obreschkow
Description: 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.
Depends: R (>= 3.00), magicaxis, MASS, rgl, LaplacesDemon