不同趨勢線類型爲每個組與gglpot2

同積我有以下數據集：不同趨勢線類型爲每個組與gglpot2

ID  LAND   nifH  AOA 
1 agricultural 2272430.26 36942400.00 
2 agricultural 2371496.98 34871000.00 
3 agricultural 1506827.26 28344300.00 
4 agricultural 3072303.99 37818300.00 
5 agricultural 822133.30 17915800.00 
6 agricultural 1323219.76 25076900.00 
7 agricultural 2832007.75 12980100.00 
8 agricultural 1642144.16 66015700.00 
9 agricultural 1917801.37 30374200.00 
10 agricultural 1091955.01 24029000.00 
11 agricultural 541873.86 7077250.00 
12 agricultural 965444.92 15828000.00 
13 agricultural 2274418.90 2768740.00 
14 agricultural 503230.31 5417750.00 
15 agricultural 1134978.51 29983100.00 
16 agricultural 1138200.48 33578500.00 
17 agricultural 2599519.18 38748600.00 
18 agricultural 830130.41 19844300.00 
19 agricultural 1718543.20 39919100.00 
20 agricultural 848999.15 31510400.00 
21 agricultural 993265.16 19315900.00 
22 agricultural 1328374.95 8704000.00 
23 agricultural 588577.99 7107390.00 
24 natural 1265534.76 11633500.00 
25 natural 1424244.23 22986800.00 
26 natural 1645932.48 74835300.00 
27 natural 794645.31 53313900.00 
28 natural 1206666.73 57958200.00 
29 natural 1194033.93 56863100.00 
30 natural 1647612.35 76749100.00 
31 natural 1373078.78 78014900.00 
32 natural 2588474.53 95331700.00 
33 natural 1709596.00 49901500.00 
34 natural 2185120.45 82679000.00 
35 natural 1614733.98 21855400.00 
36 natural 1304585.38 49941000.00 
37 agricultural 699308.20 1609450.00 
38 agricultural 443499.88 776379.06 
39 natural 501543.10 49777.59 
40 natural 83694.81 9711.16 
41 agricultural 1545325.46 13227000.00 
42 agricultural 853717.25 851032.11 
43 natural 592806.33 731260.03 
44 agricultural 274198.19 30947.01 
45 agricultural 660950.13 76135400.00 
46 agricultural 731145.76 4326470.00 
47 agricultural 946266.70 1808130.00 
48 agricultural 1262565.09 648326.92 
49 agricultural 869847.46 16870500.00 
50 agricultural 1325450.54 78977500.00

我用下面的代碼，以使AOA和NIRK之間的散點圖和陸地分組他們

p=ggplot(all_data_untransformed, aes(x = NIRK, y = AOA, colour = factor(LAND))) + 
    geom_point() + 
    stat_smooth(method = "glm", family = gaussian, se = T)

有沒有一種方法可以爲每個組執行不同的平滑方法（例如，爲A組應用gam模型，爲B組應用lm模型），併爲每個趨勢線添加R sqt？謝謝

來源

2014-10-26 mtsiknia

當然有。 'stat_smooth'有很多選項可用，請檢查這些選項，即'method'和'family'。 – tonytonov 2014-10-27 08:46:13

謝謝你的回覆！也許我在我的問題上並不是非常特別。例如，我想要爲A組應用gam模型，爲B組應用lm模型，有沒有辦法做到這一點？我認爲stat_smooth對兩組都應用相同的趨勢線方法。 – mtsiknia 2014-10-28 09:12:12

啊，我明白了。然後請將這個要求添加到問題中。 – tonytonov 2014-10-28 13:06:36

要針對不同級別有不同型號，一種解決方案是使用兩個stat_smooth()調用，然後是每個模型的子集數據。

ggplot(all_data_untransformed, aes(x = nifH, y = AOA, colour =LAND)) + 
     geom_point() + 
     stat_smooth(data=subset(all_data_untransformed,LAND=="agricultural"), 
            method = "lm", se = T) + 
     stat_smooth(data=subset(all_data_untransformed,LAND=="natural"), 
           method = "loess", se = T)

enter image description here

來源

2014-10-28 19:14:09

非常感謝！我相信子集是我正在尋找的！ – mtsiknia 2014-10-30 15:35:36

不同趨勢線類型爲每個組與gglpot2

回答

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