{ "_id": "6a1ee159b401979e734109bf", "Package": "HDMFA", "Type": "Package", "Title": "High-Dimensional Matrix Factor Analysis", "Version": "0.1.1", "Author": "Yong He [aut], Changwei Zhao [aut], Ran Zhao [aut, cre]", "Authors@R": "c(person(\"Yong\", \"He\", role = \"aut\"),\nperson(\"Changwei\", \"Zhao\", role=\"aut\"),\nperson(\"Ran\", \"Zhao\", role = c(\"aut\",\"cre\"), email=\"Zhaoran@mail.sdu.edu.cn\"))", "Maintainer": "Ran Zhao ", "Description": "High-dimensional matrix factor models have drawn much\nattention in view of the fact that observations are usually\nwell structured to be an array such as in macroeconomics and\nfinance. In addition, data often exhibit heavy-tails and thus\nit is also important to develop robust procedures. We aim to\naddress this issue by replacing the least square loss with\nHuber loss function. We propose two algorithms to do robust\nfactor analysis by considering the Huber loss. One is based on\nminimizing the Huber loss of the idiosyncratic error's\nFrobenius norm, which leads to a weighted iterative projection\napproach to compute and learn the parameters and thereby named\nas Robust-Matrix-Factor-Analysis (RMFA), see the details in He\net al. (2023). The other one\nis based on minimizing the element-wise Huber loss, which can\nbe solved by an iterative Huber regression algorithm (IHR), see\nthe details in He et al. (2023) . In this\npackage, we also provide the algorithm for alpha-PCA by Chen &\nFan (2021) , the Projected\nestimation (PE) method by Yu et al.\n(2022). In addition, the\nmethods for determining the pair of factor numbers are also\ngiven.", "License": "GPL-2 | GPL-3", "Encoding": "UTF-8", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-20 07:01:32 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-01-21 02:42:34 UTC", "RemoteUrl": "https://github.com/cran/HDMFA", "RemoteRef": "HEAD", "RemoteSha": "6520eae83301f47509039509bb15a99e2935e4b8", "MD5sum": "667e8d065f694cf2a5541d790b67dd81", "_user": "cran", "_type": "src", "_file": "HDMFA_0.1.1.tar.gz", "_fileid": "3a7e22c65ad8fa6622aa56622723724800777cf0e2bf374407b3e34dc36d20e0", "_filesize": 249541, "_sha256": "3a7e22c65ad8fa6622aa56622723724800777cf0e2bf374407b3e34dc36d20e0", "_created": "2026-05-20T07:01:32.000Z", "_published": "2026-06-02T13:57:45.951Z", "_distro": "noble", "_jobs": [ { "job": 79087929424, "time": 118, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7103346204" }, { "job": 79087929347, "time": 132, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7103349590" }, { "job": 79087929417, "time": 158, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7103312769" }, { "job": 79087928435, "time": 102, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7359783651" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/26146755800", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/HDMFA", "_commit": { "id": "6520eae83301f47509039509bb15a99e2935e4b8", "author": "Ran Zhao ", "committer": "cran-robot ", "message": "version 0.1.1\n", "time": 1705804954 }, "_maintainer": { "name": "Ran Zhao", "email": "zhaoran@mail.sdu.edu.cn" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0", "role": "Depends" }, { "package": "MASS", "role": "Imports" }, { "package": "RSpectra", "role": "Imports" } ], "_owner": "cran", "_selfowned": false, "_usedby": 1, "_updates": [], "_tags": [], "_stars": 0, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 239, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/HDMFA" }, "_searchresults": 0, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/HDMFA.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2023-05-30" }, { "version": "0.1.1", "date": "2024-01-20" } ], "_exports": [ "alpha_PCA", "KMHFA", "KPCA", "KPE", "MHFA", "PE" ], "_help": [ { "page": "alpha_PCA", "title": "Statistical Inference for High-Dimensional Matrix-Variate Factor Model", "topics": [ "alpha_PCA" ] }, { "page": "KMHFA", "title": "Estimating the Pair of Factor Numbers via Eigenvalue Ratios or Rank Minimization.", "topics": [ "KMHFA" ] }, { "page": "KPCA", "title": "Estimating the Pair of Factor Numbers via Eigenvalue Ratios Corresponding to alpha-PCA", "topics": [ "KPCA" ] }, { "page": "KPE", "title": "Estimating the Pair of Factor Numbers via Eigenvalue Ratios Corresponding to PE", "topics": [ "KPE" ] }, { "page": "MHFA", "title": "Matrix Huber Factor Analysis", "topics": [ "MHFA" ] }, { "page": "PE", "title": "Projected Estimation for Large-Dimensional Matrix Factor Models", "topics": [ "PE" ] } ], "_rundeps": [ "lattice", "MASS", "Matrix", "Rcpp", "RcppEigen", "RSpectra" ], "_score": 1.4771212547196624, "_indexed": true, "_nocasepkg": "hdmfa", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.1", "date": "2026-05-20T07:03:26.000Z", "distro": "noble", "commit": "6520eae83301f47509039509bb15a99e2935e4b8", "fileid": "f78951f92ca91b91c04532cb0e1239352c60e32d305aa2920c87a5958ea78ef9", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26146755800" }, { "r": "4.6.0", "os": "linux", "version": "0.1.1", "date": "2026-05-20T07:03:31.000Z", "distro": "noble", "commit": "6520eae83301f47509039509bb15a99e2935e4b8", "fileid": "27842996c6cdefdb14a336ac80902d37cc9941d46d00c12c546681552e39dac3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26146755800" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.1", "date": "2026-06-02T13:57:11.000Z", "commit": "6520eae83301f47509039509bb15a99e2935e4b8", "fileid": "7be719466ec96c219d3ef7f5be6d61133921efd0f2894fff35121bce9593e81e", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/26146755800" } ] }