在 R 中拟合自启动 Nls 渐近回归模型
Fit a Self-Starting Nls Asymptotic Regression Model in R
我有一个数据框df
df<-structure(list(y = c(152.264522056852, 90.1433769206633, 14.9873599316925,
234.736409910023, 60.4167695627548, 380.654850683175, 467.840079978108,
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45.6788141629659, 18.3098075923626, 51.8945797282504, 48.6587242824025,
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198.121665383659), x = c(74, 75, 77, 78, 79, 49, 50, 51, 52,
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"x"), row.names = c(719L, 720L, 721L, 722L, 723L, 724L, 725L,
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数据如下所示：
我现在正在尝试使用 R
中的 SSasympOff 函数将渐近回归模型拟合到我的数据
fit<-nls(y ~ SSasympOff(x, A, lrc, c0), data = df)
然而，尽管我认为渐近回归模型确实可以拟合我的数据，但拟合还是以某种方式失败了。任何想法出了什么问题？
解决方法很简单。我的数据应该符合 Weibull 模型。
答案如下：
fit<-nls(y ~ SSweibull(x, A, lrc, c0), data = df
我有一个数据框df
df<-structure(list(y = c(152.264522056852, 90.1433769206633, 14.9873599316925,
234.736409910023, 60.4167695627548, 380.654850683175, 467.840079978108,
358.497598990798, 431.528439198621, 442.010991849005, 351.189937948249,
343.098349086009, 357.122478995472, -518.123427070677, -554.919201846235,
-614.669225180172, -391.545088194311, -124.396037524566, 32.3765077856369,
43.199114789255, -88.3050879996736, 58.9395819107303, 162.441016515717,
116.965395963751, 13.0217520870501, 17.828320314642, -16.2957513090223,
70.6350404303521, 45.2225155929918, 103.825463471585, -47.560741043475,
-93.4213242912665, 20.1581508014351, 13.8083492300939, 5.60939206456533,
31.3564232334029, 28.6217511966825, -146.205068191513, -121.016505045118,
-115.100180697977, -82.8617020281963, -141.853484972846, -94.9308303585276,
-64.6400166181847, -66.4285516217351, -42.6337259062566, -148.123950563371,
-133.712445091456, -152.950761315413, -157.68036919646, -261.660716732062,
-179.565574658569, 130.724638285115, 291.076604684815, 121.960359405726,
164.323498383164, 348.140279591084, 129.706528767943, 93.6406692401506,
8.05810943059623, 126.535503963009, 162.629432365065, 64.9450473105535,
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46.334381384775, 91.8543458277127, 70.0609471213538, 3.19760374492034,
45.6788141629659, 18.3098075923626, 51.8945797282504, 48.6587242824025,
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198.121665383659), x = c(74, 75, 77, 78, 79, 49, 50, 51, 52,
53, 54, 55, 56, 2, 3, 4, 5, 13, 14, 15, 16, 17, 71, 72, 157,
160, 162, 163, 164, 165, 153, 154, 155, 71, 72, 73, 74, 37, 38,
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77, 78, 79, 80, 81, 82, 126, 127, 128, 129, 130, 131, 132, 71,
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66, 42, 43, 44, 45, 46, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73,
54, 55, 56, 57, 58, 59, 49, 50, 51, 52, 53, 54, 56, 64, 65, 66,
67, 68, 69, 101, 105, 106, 107, 108, 109, 34, 35, 37, 38, 39,
10, 131, 132, 133, 134, 135, 136, 137, 138, 139, 46, 47, 17,
18, 35, 36, 84, 85, 86, 87, 88, 67, 70, 72, 73)), .Names = c("y",
"x"), row.names = c(719L, 720L, 721L, 722L, 723L, 724L, 725L,
726L, 727L, 728L, 729L, 730L, 731L, 732L, 733L, 734L, 735L, 736L,
737L, 738L, 739L, 740L, 741L, 742L, 743L, 744L, 745L, 746L, 747L,
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759L, 760L, 761L, 762L, 763L, 764L, 765L, 766L, 767L, 768L, 769L,
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947L, 948L, 949L, 950L, 951L, 952L), class = "data.frame")
数据如下所示：
我现在正在尝试使用 R
中的SSasympOff 函数将渐近回归模型拟合到我的数据
fit<-nls(y ~ SSasympOff(x, A, lrc, c0), data = df)
然而，尽管我认为渐近回归模型确实可以拟合我的数据，但拟合还是以某种方式失败了。任何想法出了什么问题？
解决方法很简单。我的数据应该符合 Weibull 模型。
答案如下：
fit<-nls(y ~ SSweibull(x, A, lrc, c0), data = df