我有一个数据帧 df
df<-structure(list(P = c(794.102395099402, 1299.01021921817, 1219.80731174175,
1403.00786976395, 742.749487463385, 340.246973543409, 90.3220586792255,
195.85557320714, 199.390867672674, 191.4970921278, 334.452413539092,
251.730350291822, 235.899165861309, 442.969718728163, 471.120193046119,
458.464154601097, 950.298132134912, 454.660729622624, 591.212003320456,
546.188716055825, 976.994105334083, 1021.67000560164, 945.965200876724,
932.324768081307, 3112.60002304117, 624.005047807736, 0, 937.509240627289,
892.926195849975, 598.564015734103, 907.984807726741, 363.400837339461,
817.629824627294, 2493.75851182081, 451.149000503123, 1028.41455932241,
615.640039284434, 688.915621065535, NaN, 988.21297, NaN, 394.7,
277.7, 277.7, 492.7, 823.6, 1539.1, 556.4, 556.4, 556.4), T = c(11.7087701201175,
8.38748953516909, 9.07065637842101, 9.96978059247473, 2.87026334756687,
-1.20497751697385, 1.69057148825093, 2.79168506923385, -1.03659741363293,
-2.44619473778322, -1.0414166493637, -0.0616510891024765, -2.19566614081763,
2.101408628412, 1.30197334094966, 1.38963309876057, 1.11283280896495,
0.570385633957982, 1.05118063842584, 0.816991857384802, 8.95069454902333,
6.41067954598958, 8.42110173395973, 13.6455092557636, …我有一个数据帧df:
structure(list(y = c(2268.14043972082, 2147.62290922552, 2269.1387550775,
2247.31983098201, 1903.39138268307, 2174.78291538358, 2359.51909126411,
2488.39004804939, 212.851575751527, 461.398994384333, 567.150629704352,
781.775113821961, 918.303706148872, 1107.37695799186, 1160.80594193377,
1412.61328924168, 1689.48879626486, 260.737164468854, 306.72700499362,
283.410379620422, 366.813913489692, 387.570173754128, 388.602676983443,
477.858510450125, 128.198042456082, 535.519377609133, 1028.8780498564,
1098.54431357711, 1265.26965941035, 1129.58344809909, 820.922447928053,
749.343583476846, 779.678206156474, 646.575242339517, 733.953282899613,
461.156280127354, 906.813018662913, 798.186995701282, 831.365377249207,
764.519073183124, 672.076289062505, 669.879217186302, 1341.47673353751,
1401.44881976186, 1640.27575962036), P = c(1750.51986303926,
1614.11541634798, 951.847023338079, 1119.3682884872, 1112.38984390156,
1270.65773075982, 1234.72262170166, 1338.46096616983, 1198.95775346458,
1136.69287367165, 1265.46480803983, 1364.70149818063, 1112.37006707489,
1346.49240261316, 1740.56677791104, 1410.99217295647, 1693.18871380948,
901.760176040232, 763.971046562772, 994.8699095021, 972.755147593882,
1011.41669411398, 643.705302958842, 537.54384616157, 591.212003320456,
464.405641604215, 0, 0, …我有一个数据框df(见下文)
dput(df)
structure(list(x = c(49, 50, 51, 52, 53, 54, 55, 56, 1, 2, 3,
4, 5, 14, 15, 16, 17, 2, 3, 4, 5, 6, 10, 11, 3, 30, 64, 66, 67,
68, 69, 34, 35, 37, 39, 2, 17, 18, 99, 100, 102, 103, 67, 70,
72), y = c(2268.14043972082, 2147.62290922552, 2269.1387550775,
2247.31983098201, 1903.39138268307, 2174.78291538358, 2359.51909126411,
2488.39004804939, 212.851575751527, 461.398994384333, 567.150629704352,
781.775113821961, 918.303706148872, 1107.37695799186, 1160.80594193377,
1412.61328924168, 1689.48879626486, 260.737164468854, 306.72700499362,
283.410379620422, 366.813913489692, 387.570173754128, 388.602676983443,
477.858510450125, 128.198042456082, 535.519377609133, 1028.8780498564, …我试图在反应数据框中添加非线性回归模型和多变量分析的优势.我设法创建了反应数据帧,在我过滤数据时随时更新.我现在想要在过滤数据帧时更新模型输出,并将模型的预测值添加到反应数据帧.下面是我正在使用的数据集的子集以及我用来创建闪亮App的ui和服务器文件.
加载包
library (shiny)
library(ggvis)
library(dplyr)
library(rbokeh)
library (minpack.lm)
library (hydroGOF)
library(caret)
我使用的数据帧:
Flux_Data_df<- structure(list(Site_ID = structure(c(1L, 3L, 5L, 7L, 8L), .Label = c("AR-Slu",
"AR-Vir", "AU-Tum", "AU-Wac", "BE-Bra", "BE-Jal", "BE-Vie", "BR-Cax",
"BR-Ma2", "BR-Sa1", "BR-Sa3", "BW-Ma1", "CA-Ca1", "CA-Ca2", "CA-Ca3",
"CA-Gro", "Ca-Man", "CA-NS1", "CA-NS2", "CA-NS3", "CA-NS4", "CA-NS5",
"CA-NS6", "CA-NS7", "CA-Oas", "CA-Obs", "CA-Ojp", "CA-Qcu", "CA-Qfo",
"CA-SF1", "CA-SF2", "CA-SF3", "CA-SJ1", "CA-SJ2", "CA-SJ3", "CA-TP1",
"CA-TP2", "CA-TP3", "CA-TP4", "CA-Wp1", "CN-Bed", "CN-Cha", "CN-Din",
"CN-Ku1", "CN-Qia", "CZ-Bk1", "De-Bay", "DE-Hai", "DE-Har", "DE-Lkb",
"DE-Meh", "DE-Obe", "DE-Tha", "DE-Wet", "DK-Sor", "ES-Es1", "FI-Hyy", …