R: Multi-Site Auto-Regressive Weather GENerator

# Multi-Site Auto-Regressive Weather GENerator

## Documentation for package ‘RMAWGEN’ version 1.3.9.3

- DESCRIPTION file.

## Help Pages

RMAWGEN-package | R - Multi-site Autoregressive WEather Generator
acvWGEN | Plots the auto- and cross- covariance functions between measured and simulated data for several stations
adddate | Inserts three columns (year,month,day) passing dates to a matrix or to a dataframe
addsuffixes | Adds suffixes for daily maximum and minimum temperature to the names of a column data frame
arch_test | 'arch.test' function for 'varest2' object
collinear_dataset | Collinear Dataset
ComprehensivePrecipitationGenerator | The comprehensive Precipitation Generator
ComprehensiveTemperatureGenerator | The Comprehensive Temperature Generator
continuity_ratio | Calculates the continuity ratio of a set of precipitation measured or generated data in several sites as defined by Wilks, 1998 (see reference link)
countNAs | counts NAs in each row of 'data'
covariance | Calculates the covariance matrix of the normally standardized variables obtained from the columns of 'x'
ELEVATION | Trentino Dataset
ElevationOf | Extracts the elevation of a meteorological station expressed in meters above a reference (sea level)
extractdays | Extracts the rows of a matrix corresponding to the requested days (expressed as dates YYYY-MM-DD) given the date (origin) of the first row
extractmonths | Extracts the rows of a matrix corresponding to requested months of a year given the date (origin) of the first row
extractTnFromAnomalies | Extracts generated time series of Daily Minimum Temperature from a random multi-realization obtained by 'generateTemperatureTimeseries' function
extractTxFromAnomalies | Extracts generated time series of Daily Maximum Temperature from a random multi-realization obtained by 'generateTemperatureTimeseries' function
extractyears | Extracts the elements of a data frame corresponding to a period between 'year_min' and 'year_max' for the stations listed in 'station'
findDate | Finds the date corresponding a row index of a matrix given the date (origin) of the first row
forecastEV | Forecasts the expected value of a VAR realization given the prievious one
forecastResidual | Forecasts the residual value of a VAR realization given the white noise covariance matrix
generateTemperatureTimeseries | Returns time series of Daily Maximum and Minimum with a random multi-realization obtained by using 'newVARmultieventRealization'. This function is called by 'ComprehensiveTemperatureGenerator'.
getDailyMean | Calculates the daily means of a range of days around each date of a data frame corresponding to a period between 'year_min' and 'year_max' for stations listed in 'station'
getMonthlyMean | Calculates the monthly means of a data frame corresponding to a period between 'year_min' and 'year_max' for stations listed in 'station'
getVARmodel | Either creates a VAR model or chooses a VAR model by using VAR or VARselect commands of 'vars' package
GPCA | This function makes a Gaussianization procedure based on PCA iteration ( see 'GPCA_iteration')
GPCA-class | GPCA-class
GPCAiteration | GPCAiteration-class
GPCAiteration-class | GPCAiteration-class
GPCAvarest2 | GPCAvarest2-class
GPCAvarest2-class | GPCAvarest2-class
GPCA_iteration | This function makes an iteration of PCA-Gaussianization process
inv_GPCA | This function makes an inverse Gaussianization procedure besad on PCA iteration ( see 'inv_GPCA_iteration'
inv_GPCA_iteration | This function makes an inverse iteration of PCA-Gaussianization process
is.monthly.climate | Verifies if 'climate' represents the monthly climatology in one year, i.e 'climate' is monthly.climate type matrix whose rows represent months and each column represents a station. It is also used in 'setComprehensiveTemperatureGeneratorParameters'.
LOCATION | Trentino Dataset
months_f | months REPLACEMANT
NewVAReventRealization | Generates a new realization of a VAR model
newVARmultieventRealization | Generates several realizations of a VAR model
normality_test | 'normality.test' method for 'varest2' object
normalizeGaussian | Converts a random variable 'x' extracted by a population represented by the sample 'data' or 'sample' to a normally-distributed variable with assigned mean and standard deviation or vice versa in case 'inverse' is 'TRUE'
normalizeGaussian_prec | Converts precipitation values to "Gaussinized" normally-distributed values taking into account the probability of no precipitation occurrences. values or vice versa in case 'inverse' is 'TRUE'
normalizeGaussian_severalstations | Converts several samples 'x' random variable extracted by populations represented by the columns of 'data' respectively or 'sample' to a normally-distributed samples with assinged mean and standard deviation or vice versa in case 'inverse' is 'TRUE'
normalizeGaussian_severalstations_prec | DEPRECATED Converts several samples 'x' random variable (daily precipitation values) extracted by populations represented by the columns of 'data' respectively or 'sample' to a normally-distributed samples with assinged mean and standard deviation or vice versa in case 'inverse' is 'TRUE' using the function 'normalizeGaussian_prec'
plotDailyClimate | Plots daily climatology through one year
plot_sample | It makes a plot by sampling (e.g. monthly) the variables 'x' and 'y'
PRECIPITATION | Trentino Dataset
PrecipitationEndDay | Gets the last day in a precipitation time series, expressed in decimal julian days since 1970-1-1 00:00 UTC
PrecipitationStartDay | Gets the first day in a precipitation time series, expressed in decimal julian days since 1970-1-1 00:00 UTC
PRECIPITATION_MEASUREMENT_END_DAY | Trentino Dataset
PRECIPITATION_MEASUREMENT_START_DAY | Trentino Dataset
print | 'print' S3 method for 'GPCA' or 'GPCA_iteration' object
print.GPCA | 'print' S3 method for 'GPCA' or 'GPCA_iteration' object
print.GPCAiteration | 'print' S3 method for 'GPCA' or 'GPCA_iteration' object
qqplot.lagged | This function creates a Q-Q plot of the 'lag'-lag moving cumulative addition of the values in the samples 'x,y,z'
qqplotprecWGEN | Makes a qqplot of measured and simulated data for several stations.
qqplotprecWGEN_seasonal | Makes four seasonal qqplots (winter, spring, summer and autumn) of measured and simulated data for several stations.
qqplotTnTxWGEN | Makes a qqplot of measured and simulated data for several stations.
qqplotTnTxWGEN_seasonal | Makes four seasonal qqplots (winter, spring, summer and autumn) of measured and simulated data for several stations.
qqplotWGEN | Makes a qqplot and Wilcoxon test between the two columns of 'val'
qqplot_RMAWGEN_deltaT | It makes the Q-Q plots observed vs generated time series of daily maximum, minimum temperature and daily thermal range for a list of collected stochastic generations
qqplot_RMAWGEN_prec | It makes the Q-Q plots observed vs generated time series of daily maximum, minimum temperature and daily thermal range for a list of collected stochastic generations
qqplot_RMAWGEN_Tn | It makes the Q-Q plots observed vs generated time series of daily maximum, minimum temperature and daily thermal range for a list of collected stochastic generations
qqplot_RMAWGEN_Tx | It makes the Q-Q plots observed vs generated time series of daily maximum, minimum temperature and daily thermal range for a list of collected stochastic generations
removeNAs | Replaces each entry of the rows containing NA values with NA
rescaling_monthly | This function adjusts the monthly mean to a daily weather dataset (e. g. spline-interpolated temperature)
residuals | 'residuals' S3 method for 'varest2' object
residuals.varest2 | 'residuals' S3 method for 'varest2' object
RMAWGEN | R - Multi-site Autoregressive WEather Generator
serial_test | 'serial.test' function for 'varest2' object
setComprehensiveTemperatureGeneratorParameters | Computes climatic and correlation information useful for creating an auto-regeressive random generation of maximum and minimun daily temparature. This function is called by 'ComprehensiveTemperatureGenerator'.
splineInterpolateMonthlytoDaily | Interpolates monthly data to daily data using 'spline' and preserving monthly mean values
splineInterpolateMonthlytoDailyforSeveralYears | Interpolates monthly data to daily data using 'splineInterpolateMonthlytoDaily' for several years
STATION_LATLON | Trentino Dataset
STATION_NAMES | Trentino Dataset
TemperatureEndDay | Gets the last day in a temperature time series, expressed as decimal julian days since 1970-1-1 00:00 UTC
TemperatureStartDay | Gets the first day in a temperature time series, expressed as decimal julian days since 1970-1-1 00:00 UTC
TEMPERATURE_MAX | Trentino Dataset
TEMPERATURE_MEASUREMENT_END_DAY | Trentino Dataset
TEMPERATURE_MEASUREMENT_START_DAY | Trentino Dataset
TEMPERATURE_MIN | Trentino Dataset
trentino | Trentino Dataset
varest | varest-class
varest-class | varest-class
varest2 | varest2-class
varest2-class | varest2-class
VAR_mod | Modified version of 'VAR' function allowing to describe white-noise as VAR-(0) model (i. e. 'varest' objects)
WhereIs | Gets the toponym where a meteorological station is located