{ "_id": "6a23c886530b9bc726be0b01", "Package": "MultiKink", "Type": "Package", "Version": "0.2.0", "Title": "Estimation and Inference for Multi-Kink Quantile Regression", "Authors@R": "c(\nperson(\"Chuang\", \"Wan\", email = \"wanchuanghnu@126.com\", role = c(\"aut\", \"cre\")),\nperson(\"Wei\", \"Zhong\", email = \"wzhong@xmu.edu.cn\", role = \"aut\"))", "Description": "Estimation and inference for multiple kink quantile\nregression for longitudinal data and the i.i.d data. A\nbootstrap restarting iterative segmented quantile algorithm is\nproposed to estimate the multiple kink quantile regression\nmodel conditional on a given number of change points. The\nnumber of kinks is also allowed to be unknown. In such case,\nthe backward elimination algorithm and the bootstrap restarting\niterative segmented quantile algorithm are combined to select\nthe number of change points based on a quantile BIC. For\nlongitudinal data, we also develop the GEE estimator to\nincorporate the within-subject correlations. A score-type\nbased test statistic is also developed for testing the\nexistence of kink effect. The package is based on the paper,\n``Wei Zhong, Chuang Wan and Wenyang Zhang (2022). Estimation\nand inference for multikink quantile regression, JBES'' and\n``Chuang Wan, Wei Zhong, Wenyang Zhang and Changliang Zou\n(2022). Multi-kink quantile regression for longitudinal data\nwith application to progesterone data analysis, Biometrics\".", "License": "GPL", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.3", "NeedsCompilation": "no", "Author": "Chuang Wan [aut, cre], Wei Zhong [aut]", "Maintainer": "Chuang Wan ", "Packaged": { "Date": "2026-06-06 07:10:03 UTC", "User": "root" }, "Repository": "https://chuangwan1994.r-universe.dev", "Date/Publication": "2023-11-05 18:30:21 UTC", "RemoteUrl": "https://github.com/cran/MultiKink", "RemoteRef": "HEAD", "RemoteSha": "21a10f6a44e5d3273afe67f617c1182ea1ab4b55", "MD5sum": "47261e217fe7f164bda2498edd053fb7", "_user": "chuangwan1994", "_type": "src", "_file": "MultiKink_0.2.0.tar.gz", "_fileid": "1d099b1d4c78f34baf9aead523a6f45ff9a28bfeee31f62b7097f419b387daf8", "_filesize": 127175, "_sha256": "1d099b1d4c78f34baf9aead523a6f45ff9a28bfeee31f62b7097f419b387daf8", "_created": "2026-06-06T07:10:03.000Z", "_published": "2026-06-06T07:13:10.961Z", "_distro": 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