{ "_id": "6a211d54cd65a98ecbd1dade", "Package": "RMAWGEN", "Maintainer": "Emanuele Cordano ", "License": "GPL (>= 2)", "Title": "Multi-Site Auto-Regressive Weather GENerator", "Type": "Package", "Authors@R": "c(person(given = \"Emanuele\",\nfamily = \"Cordano\",\nrole = c(\"aut\", \"cre\",\"ctb\"),\nemail = \"emanuele.cordano@gmail.com\",comment=c(ORCID=\"0000-0002-3508-5898\")),\nperson(given = \"Emanuele\",\nfamily = \"Eccel\",\nrole = \"aut\",comment=c(ORCID=\"0000-0003-3239-828X\")),\nperson(given = \"Eike\",\nfamily = \"Luedeling\",\nrole = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-7316-3631\")))", "Description": "S3 and S4 functions are implemented for spatial multi-site\nstochastic generation of daily time series of temperature and\nprecipitation. These tools make use of Vector AutoRegressive\nmodels (VARs). The weather generator model is then saved as an\nobject and is calibrated by daily instrumental \"Gaussianized\"\ntime series through the 'vars' package tools. Once obtained\nthis model, it can it can be used for weather generations and\nbe adapted to work with several climatic monthly time series.", "Version": "1.3.9.3", "Date": "2025-04-08", "URL": "https://ecor.github.io/RMAWGEN/,https://github.com/ecor/RMAWGEN,\nhttps://docs.google.com/file/d/0B66otCUk3Bv6V3RPbm1mUG4zVHc/edit", "RoxygenNote": "7.3.2", "Repository": "https://ecor.r-universe.dev", "Date/Publication": "2025-04-12 16:42:18 UTC", "RemoteUrl": "https://github.com/ecor/rmawgen", "RemoteRef": "HEAD", "RemoteSha": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-04 06:35:27 UTC", "User": "root" }, "Author": "Emanuele Cordano [aut, cre, ctb] (ORCID:\n),\nEmanuele Eccel [aut] (ORCID: ),\nEike Luedeling [ctb] (ORCID: )", "MD5sum": "e4258e1a63a894bba0efce59cfce8cdc", "_user": "ecor", "_type": "src", "_file": "RMAWGEN_1.3.9.3.tar.gz", "_fileid": "b53e9adbe1a5080f5356cc457352010475fea993e563515508c98f6dbc41fd5a", "_filesize": 2066935, "_sha256": "b53e9adbe1a5080f5356cc457352010475fea993e563515508c98f6dbc41fd5a", "_created": "2026-06-04T06:35:27.000Z", "_published": "2026-06-04T06:38:12.809Z", "_distro": "noble", "_jobs": [ { "job": 79463347407, "time": 127, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7404667549" }, { "job": 79463347451, "time": 124, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7404666757" }, { "job": 79463347456, "time": 106, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7404661109" }, { "job": 79463347414, "time": 120, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7404665150" }, { "job": 79462980321, "time": 167, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7404632359" }, { "job": 79463347399, "time": 98, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7404659288" }, { "job": 79463347440, "time": 99, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7404659800" }, { "job": 79463347478, "time": 97, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7404659086" }, { "job": 79463347529, "time": 112, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7404663381" } ], "_buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/ecor/rmawgen", "_commit": { "id": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "author": "Emanuele Cordano ", "committer": "Emanuele Cordano ", "message": "on CRAN\n", "time": 1744476138 }, "_maintainer": { "name": "Emanuele Cordano", "email": "emanuele.cordano@gmail.com", "login": "ecor", "orcid": "0000-0002-3508-5898", "description": "I’m an environmental engineer with hydraulic and hydrological background and some skills in programming. Actually I'm self-employed and also work at JRC Ispra.", "uuid": 4470657 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "chron", "role": "Depends" }, { "package": "date", "role": "Depends" }, { "package": "vars", "role": "Depends" }, { "package": "methods", "role": "Depends" }, { "package": "Matrix", "role": "Imports" }, { "package": "lubridate", "role": "Suggests" } ], "_owner": "ecor", "_selfowned": true, "_usedby": 4, "_updates": [], "_tags": [], "_stars": 4, "_contributors": [ { "user": "ecor", "count": 47, "uuid": 4470657 }, { "user": "eikeluedeling", "count": 1, "uuid": 9819816 } ], "_userbio": { "uuid": 4470657, "type": "user", "name": "Emanuele Cordano", "description": "I’m an environmental engineer with hydraulic and hydrological background and some skills in programming. Actually I'm self-employed and also work at JRC Ispra." }, "_downloads": { "count": 675, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/RMAWGEN" }, "_devurl": "https://github.com/ecor/rmawgen", "_pkgdown": "https://ecor.github.io/RMAWGEN/", "_searchresults": 102, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/readme.html", "extra/readme.md", "extra/RMAWGEN.html", "manual.pdf" ], "_homeurl": "https://github.com/ecor/rmawgen", "_realowner": "ecor", "_cranurl": true, "_releases": [ { "version": "1.0", "date": "2011-08-12" }, { "version": "1.1", "date": "2011-09-28" }, { "version": "1.2", "date": "2011-12-22" }, { "version": "1.2.1", "date": "2012-01-14" }, { "version": "1.2.2", "date": "2012-02-21" }, { "version": "1.2.4", "date": "2012-04-05" }, { "version": "1.2.5", "date": "2012-05-11" }, { "version": "1.2.5.1", "date": "2012-06-13" }, { "version": "1.2.5.3", "date": "2012-08-14" }, { "version": "1.2.5.4", "date": "2013-04-24" }, { "version": "1.2.5.5", "date": "2013-05-23" }, { "version": "1.2.6", "date": "2014-01-17" }, { "version": "1.2.6.1", "date": "2014-04-29" }, { "version": "1.3.0", "date": "2014-12-20" }, { "version": "1.3.3", "date": "2017-02-11" }, { "version": "1.3.6", "date": "2019-11-15" }, { "version": "1.3.7", "date": "2019-12-12" }, { "version": "1.3.9.3", "date": "2025-04-12" } ], "_exports": [ "acvWGEN", "adddate", "addsuffixes", "arch_test", "ComprehensivePrecipitationGenerator", "ComprehensiveTemperatureGenerator", "continuity_ratio", "covariance", "ElevationOf", "extractdays", "extractmonths", "extractTnFromAnomalies", "extractTxFromAnomalies", "extractyears", "findDate", "forecastResidual", "generateTemperatureTimeseries", "getDailyMean", "getMonthlyMean", "getVARmodel", "GPCA", "GPCA_iteration", "inv_GPCA", "inv_GPCA_iteration", "is.monthly.climate", "months_f", "NewVAReventRealization", "newVARmultieventRealization", "normality_test", "normalizeGaussian", "normalizeGaussian_prec", "normalizeGaussian_severalstations", "normalizeGaussian_severalstations_prec", "plot_sample", "plotDailyClimate", "PrecipitationEndDay", "PrecipitationStartDay", "qqplot_RMAWGEN_deltaT", "qqplot_RMAWGEN_prec", "qqplot_RMAWGEN_Tn", "qqplot_RMAWGEN_Tx", "qqplot.lagged", "qqplotprecWGEN", "qqplotprecWGEN_seasonal", "qqplotTnTxWGEN", "qqplotTnTxWGEN_seasonal", "qqplotWGEN", "removeNAs", "serial_test", "setComprehensiveTemperatureGeneratorParameters", "splineInterpolateMonthlytoDaily", "splineInterpolateMonthlytoDailyforSeveralYears", "TemperatureEndDay", "VAR_mod", "WhereIs" ], "_datasets": [ { "name": "collinear_dataset", "title": "Collinear Dataset", "object": "collinear_dataset", "file": "collinear_dataset.rda", "class": [ "data.frame" ], "fields": [ "variable01", "variable02", "variable03", "variable04", "variable05", "variable06", "variable07", "variable08", "variable09", "variable10", "variable11", "variable12", "variable13", "variable14", "variable15", "variable16" ], "rows": 13, "table": true, "tojson": true }, { "name": "ELEVATION", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "LOCATION", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "PRECIPITATION", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "data.frame" ], "fields": [ "month", "day", "year", "T0001", "T0010", "T0014", "T0018", "T0021", "T0024", "T0032", "T0064", "T0074", "T0082", "T0083", "T0090", "T0092", "T0094", "T0099", "T0102", "T0103", "T0110", "T0129", "T0139", "T0147", "T0149", "T0150", "T0152", "T0154", "T0157", "T0160", "T0163", "T0166", "T0168", "T0169", "T0172", "T0175", "T0179", "T0189", "T0193", "T0204", "T0210", "T0211", "T0236", "T0327", "T0355", "T0360", "T0367", "T0370", "T0373", "B2440", "B6130", "B7810", "B8570", "B9100", "LFORN", "LAVIO", "LVACC", "VBARD", "VCAST", "VDOLC", "SMICH", "POLSA" ], "rows": 18262, "table": true, "tojson": false }, { "name": "PRECIPITATION_MEASUREMENT_END_DAY", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "PRECIPITATION_MEASUREMENT_START_DAY", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "STATION_LATLON", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "matrix", "array" ], "fields": {}, "rows": 59, "table": true, "tojson": true }, { "name": "STATION_NAMES", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "TEMPERATURE_MAX", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "data.frame" ], "fields": [ "month", "day", "year", "T0001", "T0010", "T0014", "T0018", "T0021", "T0024", "T0032", "T0064", "T0074", "T0082", "T0083", "T0090", "T0092", "T0094", "T0099", "T0102", "T0103", "T0110", "T0129", "T0139", "T0147", "T0149", "T0150", "T0152", "T0154", "T0157", "T0160", "T0163", "T0166", "T0168", "T0169", "T0172", "T0175", "T0179", "T0189", "T0193", "T0204", "T0210", "T0211", "T0236", "T0327", "T0355", "T0360", "T0367", "T0370", "T0373", "B2440", "B6130", "B7810", "B8570", "B9100", "LFORN", "LAVIO", "LVACC", "VBARD", "VCAST", "VDOLC", "SMICH", "POLSA" ], "rows": 18262, "table": true, "tojson": false }, { "name": "TEMPERATURE_MEASUREMENT_END_DAY", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "TEMPERATURE_MEASUREMENT_START_DAY", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "TEMPERATURE_MIN", "title": "Trentino Dataset", "object": "trentino", "file": "trentino.rda", "class": [ "data.frame" ], "fields": [ "month", "day", "year", "T0001", "T0010", "T0014", "T0018", "T0021", "T0024", "T0032", "T0064", "T0074", "T0082", "T0083", "T0090", "T0092", "T0094", "T0099", "T0102", "T0103", "T0110", "T0129", "T0139", "T0147", "T0149", "T0150", "T0152", "T0154", "T0157", "T0160", "T0163", "T0166", "T0168", "T0169", "T0172", "T0175", "T0179", "T0189", "T0193", "T0204", "T0210", "T0211", "T0236", "T0327", "T0355", "T0360", "T0367", "T0370", "T0373", "B2440", "B6130", "B7810", "B8570", "B9100", "LFORN", "LAVIO", "LVACC", "VBARD", "VCAST", "VDOLC", "SMICH", "POLSA" ], "rows": 18262, "table": true, "tojson": false } ], "_help": [ { "page": "RMAWGEN-package", "title": "R - Multi-site Autoregressive WEather Generator", "topics": [ "RMAWGEN-package", "RMAWGEN" ] }, { "page": "acvWGEN", "title": "Plots the auto- and cross- covariance functions between measured and simulated data for several stations", "topics": [ "acvWGEN" ] }, { "page": "adddate", "title": "Inserts three columns (year,month,day) passing dates to a matrix or to a dataframe", "topics": [ "adddate" ] }, { "page": "addsuffixes", "title": "Adds suffixes for daily maximum and minimum temperature to the names of a column data frame", "topics": [ "addsuffixes" ] }, { "page": "arch_test", "title": "'arch.test' function for 'varest2' object", "topics": [ "arch_test" ] }, { "page": "collinear_dataset", "title": "Collinear Dataset", "topics": [ "collinear_dataset" ] }, { "page": "ComprehensivePrecipitationGenerator", "title": "The comprehensive Precipitation Generator", "topics": [ "ComprehensivePrecipitationGenerator" ] }, { "page": "ComprehensiveTemperatureGenerator", "title": "The Comprehensive Temperature Generator", "topics": [ "ComprehensiveTemperatureGenerator" ] }, { "page": "continuity_ratio", "title": "Calculates the continuity ratio of a set of precipitation measured or generated data in several sites as defined by Wilks, 1998 (see reference link)", "topics": [ "continuity_ratio" ] }, { "page": "countNAs", "title": "counts NAs in each row of 'data'", "topics": [ "countNAs" ] }, { "page": "covariance", "title": "Calculates the covariance matrix of the normally standardized variables obtained from the columns of 'x'", "topics": [ "covariance" ] }, { "page": "ElevationOf", "title": "Extracts the elevation of a meteorological station expressed in meters above a reference (sea level)", "topics": [ "ElevationOf" ] }, { "page": "extractdays", "title": "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", "topics": [ "extractdays" ] }, { "page": "extractmonths", "title": "Extracts the rows of a matrix corresponding to requested months of a year given the date (origin) of the first row", "topics": [ "extractmonths" ] }, { "page": "extractTnFromAnomalies", "title": "Extracts generated time series of Daily Minimum Temperature from a random multi-realization obtained by 'generateTemperatureTimeseries' function", "topics": [ "extractTnFromAnomalies" ] }, { "page": "extractTxFromAnomalies", "title": "Extracts generated time series of Daily Maximum Temperature from a random multi-realization obtained by 'generateTemperatureTimeseries' function", "topics": [ "extractTxFromAnomalies" ] }, { "page": "extractyears", "title": "Extracts the elements of a data frame corresponding to a period between 'year_min' and 'year_max' for the stations listed in 'station'", "topics": [ "extractyears" ] }, { "page": "findDate", "title": "Finds the date corresponding a row index of a matrix given the date (origin) of the first row", "topics": [ "findDate" ] }, { "page": "forecastEV", "title": "Forecasts the expected value of a VAR realization given the prievious one", "topics": [ "forecastEV" ] }, { "page": "forecastResidual", "title": "Forecasts the residual value of a VAR realization given the white noise covariance matrix", "topics": [ "forecastResidual" ] }, { "page": "generateTemperatureTimeseries", "title": "Returns time series of Daily Maximum and Minimum with a random multi-realization obtained by using 'newVARmultieventRealization'. This function is called by 'ComprehensiveTemperatureGenerator'.", "topics": [ "generateTemperatureTimeseries" ] }, { "page": "getDailyMean", "title": "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'", "topics": [ "getDailyMean" ] }, { "page": "getMonthlyMean", "title": "Calculates the monthly means of a data frame corresponding to a period between 'year_min' and 'year_max' for stations listed in 'station'", "topics": [ "getMonthlyMean" ] }, { "page": "getVARmodel", "title": "Either creates a VAR model or chooses a VAR model by using VAR or VARselect commands of 'vars' package", "topics": [ "getVARmodel" ] }, { "page": "GPCA", "title": "This function makes a Gaussianization procedure based on PCA iteration ( see 'GPCA_iteration')", "topics": [ "GPCA" ] }, { "page": "GPCA_iteration", "title": "This function makes an iteration of PCA-Gaussianization process", "topics": [ "GPCA_iteration" ] }, { "page": "GPCA-class", "title": "GPCA-class", "topics": [ "GPCA-class" ] }, { "page": "GPCAiteration-class", "title": "GPCAiteration-class", "topics": [ "GPCAiteration", "GPCAiteration-class" ] }, { "page": "GPCAvarest2-class", "title": "GPCAvarest2-class", "topics": [ "GPCAvarest2", "GPCAvarest2-class" ] }, { "page": "inv_GPCA", "title": "This function makes an inverse Gaussianization procedure besad on PCA iteration ( see 'inv_GPCA_iteration'", "topics": [ "inv_GPCA" ] }, { "page": "inv_GPCA_iteration", "title": "This function makes an inverse iteration of PCA-Gaussianization process", "topics": [ "inv_GPCA_iteration" ] }, { "page": "is.monthly.climate", "title": "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'.", "topics": [ "is.monthly.climate" ] }, { "page": "months_f", "title": "months REPLACEMANT", "topics": [ "months_f" ] }, { "page": "NewVAReventRealization", "title": "Generates a new realization of a VAR model", "topics": [ "NewVAReventRealization" ] }, { "page": "newVARmultieventRealization", "title": "Generates several realizations of a VAR model", "topics": [ "newVARmultieventRealization" ] }, { "page": "normality_test", "title": "'normality.test' method for 'varest2' object", "topics": [ "normality_test" ] }, { "page": "normalizeGaussian", "title": "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'", "topics": [ "normalizeGaussian" ] }, { "page": "normalizeGaussian_prec", "title": "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'", "topics": [ "normalizeGaussian_prec" ] }, { "page": "normalizeGaussian_severalstations", "title": "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'", "topics": [ "normalizeGaussian_severalstations" ] }, { "page": "normalizeGaussian_severalstations_prec", "title": "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'", "topics": [ "normalizeGaussian_severalstations_prec" ] }, { "page": "plot_sample", "title": "It makes a plot by sampling (e.g. monthly) the variables 'x' and 'y'", "topics": [ "plot_sample" ] }, { "page": "plotDailyClimate", "title": "Plots daily climatology through one year", "topics": [ "plotDailyClimate" ] }, { "page": "PrecipitationEndDay", "title": "Gets the last day in a precipitation time series, expressed in decimal julian days since 1970-1-1 00:00 UTC", "topics": [ "PrecipitationEndDay" ] }, { "page": "PrecipitationStartDay", "title": "Gets the first day in a precipitation time series, expressed in decimal julian days since 1970-1-1 00:00 UTC", "topics": [ "PrecipitationStartDay" ] }, { "page": "print", "title": "'print' S3 method for 'GPCA' or 'GPCA_iteration' object", "topics": [ "print", "print.GPCA", "print.GPCAiteration" ] }, { "page": "qqplot_RMAWGEN_Tx", "title": "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", "topics": [ "qqplot_RMAWGEN_deltaT", "qqplot_RMAWGEN_prec", "qqplot_RMAWGEN_Tn", "qqplot_RMAWGEN_Tx" ] }, { "page": "qqplot.lagged", "title": "This function creates a Q-Q plot of the 'lag'-lag moving cumulative addition of the values in the samples 'x,y,z'", "topics": [ "qqplot.lagged" ] }, { "page": "qqplotprecWGEN", "title": "Makes a qqplot of measured and simulated data for several stations.", "topics": [ "qqplotprecWGEN" ] }, { "page": "qqplotprecWGEN_seasonal", "title": "Makes four seasonal qqplots (winter, spring, summer and autumn) of measured and simulated data for several stations.", "topics": [ "qqplotprecWGEN_seasonal" ] }, { "page": "qqplotTnTxWGEN", "title": "Makes a qqplot of measured and simulated data for several stations.", "topics": [ "qqplotTnTxWGEN" ] }, { "page": "qqplotTnTxWGEN_seasonal", "title": "Makes four seasonal qqplots (winter, spring, summer and autumn) of measured and simulated data for several stations.", "topics": [ "qqplotTnTxWGEN_seasonal" ] }, { "page": "qqplotWGEN", "title": "Makes a qqplot and Wilcoxon test between the two columns of 'val'", "topics": [ "qqplotWGEN" ] }, { "page": "removeNAs", "title": "Replaces each entry of the rows containing NA values with NA", "topics": [ "removeNAs" ] }, { "page": "rescaling_monthly", "title": "This function adjusts the monthly mean to a daily weather dataset (e. g. spline-interpolated temperature)", "topics": [ "rescaling_monthly" ] }, { "page": "residuals", "title": "'residuals' S3 method for 'varest2' object", "topics": [ "residuals", "residuals.varest2" ] }, { "page": "serial_test", "title": "'serial.test' function for 'varest2' object", "topics": [ "serial_test" ] }, { "page": "setComprehensiveTemperatureGeneratorParameters", "title": "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'.", "topics": [ "setComprehensiveTemperatureGeneratorParameters" ] }, { "page": "splineInterpolateMonthlytoDaily", "title": "Interpolates monthly data to daily data using 'spline' and preserving monthly mean values", "topics": [ "splineInterpolateMonthlytoDaily" ] }, { "page": "splineInterpolateMonthlytoDailyforSeveralYears", "title": "Interpolates monthly data to daily data using 'splineInterpolateMonthlytoDaily' for several years", "topics": [ "splineInterpolateMonthlytoDailyforSeveralYears" ] }, { "page": "TemperatureEndDay", "title": "Gets the last day in a temperature time series, expressed as decimal julian days since 1970-1-1 00:00 UTC", "topics": [ "TemperatureEndDay" ] }, { "page": "TemperatureStartDay", "title": "Gets the first day in a temperature time series, expressed as decimal julian days since 1970-1-1 00:00 UTC", "topics": [ "TemperatureStartDay" ] }, { "page": "trentino", "title": "Trentino Dataset", "topics": [ "ELEVATION", "LOCATION", "PRECIPITATION", "PRECIPITATION_MEASUREMENT_END_DAY", "PRECIPITATION_MEASUREMENT_START_DAY", "STATION_LATLON", "STATION_NAMES", "TEMPERATURE_MAX", "TEMPERATURE_MEASUREMENT_END_DAY", "TEMPERATURE_MEASUREMENT_START_DAY", "TEMPERATURE_MIN", "trentino" ] }, { "page": "VAR_mod", "title": "Modified version of 'VAR' function allowing to describe white-noise as VAR-(0) model (i. e. 'varest' objects)", "topics": [ "VAR_mod" ] }, { "page": "varest-class", "title": "varest-class", "topics": [ "varest", "varest-class" ] }, { "page": "varest2-class", "title": "varest2-class", "topics": [ "varest2", "varest2-class" ] }, { "page": "WhereIs", "title": "Gets the toponym where a meteorological station is located", "topics": [ "WhereIs" ] } ], "_readme": "https://github.com/ecor/rmawgen/raw/HEAD/README.md", "_rundeps": [ "chron", "date", "lattice", "lmtest", "MASS", "Matrix", "nlme", "sandwich", "strucchange", "urca", "vars", "zoo" ], "_score": 5.388811413473524, "_indexed": true, "_nocasepkg": "rmawgen", "_universes": [ "ecor" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.3.9.3", "date": "2026-06-04T06:37:24.000Z", "distro": "noble", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "a0acba1e8717f1d46eecbcf459c401d2bdf9cad4514b4f0094797eae904f7881", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.6.0", "os": "linux", "version": "1.3.9.3", "date": "2026-06-04T06:37:21.000Z", "distro": "noble", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "8a986540efbe13c593a3a7c973209e79f88caf2a4f89f221b36ac93ffb88a701", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.5.3", "os": "mac", "version": "1.3.9.3", "date": "2026-06-04T06:37:11.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "027b6f186d2ec9c3fd37aa7d2057a4e4e1fae7d6eb371a9a55e2cfba0714899a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.6.0", "os": "mac", "version": "1.3.9.3", "date": "2026-06-04T06:37:19.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "20a38738a2fb6f0bbc974a2f96242e34cc871f8142e5f16af02a6dcd5016c0fb", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.6.0", "os": "wasm", "version": "1.3.9.3", "date": "2026-06-04T06:37:28.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "5dfd5d88cc7c319b448dd508d11b2762f728a2f314040ede368c26eef78a8763", "status": "success", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.7.0", "os": "win", "version": "1.3.9.3", "date": "2026-06-04T06:36:54.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "1ab9a706985a1269a22f26607db9cdbdcc7e820245b9f2c0dd77743853aebc8c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.5.3", "os": "win", "version": "1.3.9.3", "date": "2026-06-04T06:36:48.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "ef66dcfafd8282ba3b7398bc7a39bd060decd4901d89abe50887a761c52b8dee", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" }, { "r": "4.6.0", "os": "win", "version": "1.3.9.3", "date": "2026-06-04T06:36:54.000Z", "commit": "24883e298709dd0d948b3f5cec68302c93f4b9c3", "fileid": "b8532780713569a34c20de00bdc026cc9e1081d7b0a5516b6be9f9f0b7486643", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/ecor/actions/runs/26935123777" } ] }