{ "_id": "6a27c0c224555f66ed53d1a9", "Package": "weatherindices", "Title": "Calculate Weather Indices", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Akhilesh Kumar\", \"Gupta\",,\"akhileshgupta.ouat@gmail.com\",\nrole = c(\"aut\",\"cph\",\"cre\"),comment = c(ORCID = \"0000-0001-9380-1103\")),\nperson(\"Kader Ali\", \"Sarkar\",,\"kader804@gmail.com\", role =\"ths\"),\nperson(\"Digvijay Singh\", \"Dhakre\",,\"dhakreds@gmail.com\", role = \"ths\"),\nperson(\"Debasis\", \"Bhattacharya\",,\"debasis_us@yahoo.com\", role = \"ths\"))", "Description": "Weather indices represent the overall weekly effect of a\nweather variable on crop yield throughout the cropping season.\nThis package contains functions that can convert the weekly\nweather data into yearly weighted Weather indices with weights\nbeing the correlation coefficient between weekly weather data\nover the years and crop yield over the years. This can be done\nfor an individual weather variable and for two weather\nvariables at a time as the interaction effect. This method was\nfirst devised by Jain, RC, Agrawal R, and Jha, MP (1980),\n\"Effect of climatic variables on rice yield and its\nforecast\",MAUSAM, 31(4), 591–596,\n. Later, the method have been\nused by various researchers and the latest can found in Gupta,\nAK, Sarkar, KA, Dhakre, DS, & Bhattacharya, D (2022), \"Weather\nBased Potato Yield Modelling using Statistical and Machine\nLearning Technique\",Environment and Ecology, 40(3B),\n1444–1449,.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.1.2", "LazyData": "true", "Config/testthat/edition": "3", "Repository": "https://akstat21.r-universe.dev", "Date/Publication": "2023-05-12 19:49:36 UTC", "RemoteUrl": "https://github.com/akstat21/weatherindices", "RemoteRef": "HEAD", "RemoteSha": "0958947409f90cd0ba23642ec94e73234a64d55e", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-09 07:10:44 UTC", "User": "root" }, "Author": "Akhilesh Kumar Gupta [aut, cph, cre] (ORCID:\n),\nKader Ali Sarkar [ths],\nDigvijay Singh Dhakre [ths],\nDebasis Bhattacharya [ths]", "Maintainer": "Akhilesh Kumar Gupta ", "MD5sum": "d8e6c2fa26a6d5bf76f28cf94a98ad20", 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modelling", "uuid": 93115120, "orcid": "0000-0001-9380-1103" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.10", "role": "Depends" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "akstat21", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "akstat21", "count": 11, "uuid": 93115120 } ], "_userbio": { "uuid": 93115120, "type": "user", "name": "Akhilesh Kumar Gupta", "description": "Time series analysis, machine learning, statistical modelling" }, "_downloads": { "count": 129, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/weatherindices" }, "_devurl": "https://github.com/akstat21/weatherindices", "_searchresults": 2, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", 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