RMAWGEN1.3.7 package

Multi-Site Auto-Regressive Weather GENerator

Plots the auto- and cross- covariance functions between measured and s...

Inserts three columns (year,month,day) passing dates to a matrix or to...

Adds suffixes for daily maximum and minimum temperature to the names o...

`arch.test`

function for `varest2`

object

The comprehensive Precipitation Generator

The Comprehensive Temperature Generator

Calculates the continuity ratio of a set of precipitation measured or ...

counts NAs in each row of `data`

Calculates the covariance matrix of the normally standardized variable...

Extracts the elevation of a meteorological station expressed in meters...

Extracts the rows of a matrix corresponding to the requested days (exp...

Extracts the rows of a matrix corresponding to requested months of a y...

Extracts generated time series of Daily Minimum Temperature from a ran...

Extracts generated time series of Daily Maximum Temperature from a ran...

Extracts the elements of a data frame corresponding to a period betwee...

Finds the date corresponding a row index of a matrix given the date (o...

Forecasts the expected value of a VAR realization given the prievious ...

Forecasts the residual value of a VAR realization given the white nois...

Returns time series of Daily Maximum and Minimum with a random multi-r...

Calculates the daily means of a range of days around each date of a da...

Calculates the monthly means of a data frame corresponding to a period...

Either creates a VAR model or chooses a VAR model by using VAR or VARs...

GPCA-class

This function makes a Gaussianization procedure based on PCA iteration...

This function makes an iteration of PCA-Gaussianization process

GPCAiteration-class

GPCAvarest2-class

This function makes an inverse Gaussianization procedure besad on PCA ...

This function makes an inverse iteration of PCA-Gaussianization proces...

Verifies if 'climate' represents the monthly climatology in one year, ...

months REPLACEMANT

Generates a new realization of a VAR model

Generates several realizations of a VAR model

`normality.test`

method for `varest2`

object

Converts a random variable `x`

extracted by a population represented b...

Converts precipitation values to "Gaussinized" normally-distributed va...

Converts several samples `x`

random variable extracted by populations ...

DEPRECATED Converts several samples `x`

random variable (daily precipi...

It makes a plot by sampling (e.g. monthly) the variables `x`

and `y`

Plots daily climatology through one year

Gets the last day in a precipitation time series, expressed in decimal...

Gets the first day in a precipitation time series, expressed in decima...

`print`

S3 method for `GPCA`

or `GPCA_iteration`

object

This function creates a Q-Q plot of the `lag`

-lag moving cumulative ad...

It makes the Q-Q plots observed vs generated time series of daily maxi...

Makes a qqplot of measured and simulated data for several stations.

Makes four seasonal qqplots (winter, spring, summer and autumn) of mea...

Makes a qqplot of measured and simulated data for several stations.

Makes four seasonal qqplots (winter, spring, summer and autumn) of mea...

Makes a qqplot and Wilcoxon test between the two columns of `val`

Replaces each entry of the rows containing NA values with NA

This function adjusts the monthly mean to a daily weather dataset (e. ...

`residuals`

S3 method for `varest2`

object

R - Multi-site Autoregressive WEather Generator

`serial.test`

function for `varest2`

object

Computes climatic and correlation information useful for creating an a...

Interpolates monthly data to daily data using `spline`

and preserving ...

Interpolates monthly data to daily data using `splineInterpolateMonthl...

Gets the last day in a temperature time series, expressed as decimal j...

Gets the first day in a temperature time series, expressed as decimal ...

Modified version of `VAR`

function allowing to describe white-noise as...

varest-class

varest2-class

Gets the toponym where a meteorological station is located

S3 and S4 functions are implemented for spatial multi-site stochastic generation of daily time series of temperature and precipitation. These tools make use of Vector AutoRegressive models (VARs). The weather generator model is then saved as an object and is calibrated by daily instrumental "Gaussianized" time series through the 'vars' package tools. Once obtained this model, it can it can be used for weather generations and be adapted to work with several climatic monthly time series.

Maintainer: Emanuele Cordano License: GPL (>= 2) Last published: 2019-12-12

Useful links