thêm bóng râm vào R lineplot biểu thị lỗi chuẩn

Question

Tôi đang tìm giải pháp R hoặc ggplot2 để vẽ đường kẻ có bóng che biểu thị lỗi chuẩn. Đã được google'd một thời gian mà không may mắn.

Có ai có kinh nghiệm tương tự và muốn chia sẻ sẽ được đánh giá.

Mẫu mã tôi đã sử dụng:

> dat <- read.table('sample',header=TRUE) 
> ggplot(dat, aes(x=pos,y=value, colour=type))+geom_line() 

Con số này tôi tạo ra:

mẫu dữ liệu:

pos value type 
1 1.40685064701 A 
2 1.58314330023 A 
3 1.74204838899 A 
4 1.61736939797 A 
5 1.29508580767 A 
6 1.09467905031 A 
7 1.10472385941 A 
8 1.02381316251 A 
9 1.30213436484 A 
10 1.70752481609 A 
11 2.01875034644 A 
12 1.82218601208 A 
13 1.46976809915 A 
14 1.78802276311 A 
15 1.93459128836 A 
16 1.95665864564 A 
17 1.57026992442 A 
18 1.15962402775 A 
19 1.05305484021 A 
20 0.919362594185 A 
21 0.833060897559 A 
22 0.77778822023 A 
23 0.980084775745 A 
24 1.32114351777 A 
25 1.55352963275 A 
26 1.57375922815 A 
27 1.14493868782 A 
28 0.25294849907 A 
29 -0.40599118604 A 
30 -0.487054890978 A 
31 -0.333389189047 A 
32 -0.226405253731 A 
33 -0.24558780059 A 
34 -0.180403027022 A 
35 -0.266733706191 A 
36 -0.0762920840723 A 
37 0.465100892866 A 
38 0.516633798421 A 
39 0.644986315681 A 
40 1.09115362242 A 
41 1.08889196437 A 
42 0.862434726048 A 
43 0.604042272774 A 
44 0.328584834197 A 
45 0.598617257523 A 
46 1.05219653601 A 
47 1.10798332527 A 
48 0.948151198722 A 
49 0.546516443068 A 
50 0.291735961134 A 
51 0.238335006253 A 
52 0.425304707962 A 
53 0.817302425729 A 
54 1.38852220304 A 
55 2.34024990348 A 
56 3.09941186364 A 
57 4.06854366458 A 
58 4.82115051043 A 
59 4.55199542056 A 
60 6.17279510607 A 
61 10.3162999798 A 
62 12.996627449 A 
63 12.2731258622 A 
64 10.8544867366 A 
65 8.27264346102 A 
66 5.79180739043 A 
67 4.81947524098 A 
68 4.19372954801 A 
69 3.46244417879 A 
70 2.69421581749 A 
71 1.93753362259 A 
72 1.54011797412 A 
73 1.29959330498 A 
74 1.21705330118 A 
75 1.22382555287 A 
76 0.952475753311 A 
77 0.686398680367 A 
78 0.747237736846 A 
79 0.720306209509 A 
80 0.463068694886 A 
81 0.306876218733 A 
82 0.121617637342 A 
83 0.0460331524847 A 
84 -0.0107323735891 A 
85 -0.0629997057801 A 
86 -0.19204582316 A 
87 -0.371375773255 A 
88 -0.42668686684 A 
89 -0.326517894916 A 
90 -0.277301361031 A 
91 -0.0386177879973 A 
92 0.0101084138435 A 
93 0.0605269021344 A 
94 0.182751080385 A 
95 0.13310933252 A 
96 0.27074048104 A 
97 0.267598260699 A 
98 0.349363089715 A 
99 0.264445135486 A 
100 0.218924366626 A 
101 0.153338812341 A 
102 -0.0679742801523 A 
103 -0.30849875963 A 
104 -0.28903625474 A 
105 -0.188860043325 A 
106 -0.204777388005 A 
107 -0.1461100225 A 
108 0.102433799309 A 
109 0.122246106735 A 
110 -0.105920831771 A 
111 -0.21545039794 A 
112 -0.135846098251 A 
113 -0.105900152586 A 
114 -0.247196889682 A 
115 -0.312824264065 A 
116 -0.251182865438 A 
117 -0.0867113506532 A 
118 0.00458490479941 A 
119 -0.0960520134953 A 
120 -0.235300588181 A 
1 0.939235632937 A 
2 1.28838263139 A 
3 1.42730334901 A 
4 1.22224614063 A 
5 0.896759827332 A 
6 0.642894836093 A 
7 0.737029720141 A 
8 0.774643396412 A 
9 0.759420758029 A 
10 1.04696772347 A 
11 1.23504525458 A 
12 1.0676601916 A 
13 0.826029313299 A 
14 1.14629521568 A 
15 1.14142924359 A 
16 1.22956581755 A 
17 1.13136892357 A 
18 0.800448368445 A 
19 0.652191202322 A 
20 0.498096263495 A 
21 0.555339022027 A 
22 0.545965232595 A 
23 0.726231857788 A 
24 0.849494247969 A 
25 0.916259379894 A 
26 0.879335232046 A 
27 0.56575342831 A 
28 0.108604596914 A 
29 -0.225555689899 A 
30 -0.320456274731 A 
31 -0.230459986895 A 
32 -0.042388319738 A 
33 -0.0833366171628 A 
34 -0.0460734786257 A 
35 -0.229033279226 A 
36 -0.175845833699 A 
37 0.197716175342 A 
38 0.28980276875 A 
39 0.512487189675 A 
40 0.683324573043 A 
41 0.631659584895 A 
42 0.522329104013 A 
43 0.393330574908 A 
44 0.168841230084 A 
45 0.350442790229 A 
46 0.72946349718 A 
47 0.925052059705 A 
48 0.821386076473 A 
49 0.505908860228 A 
50 0.297370018812 A 
51 0.212971428154 A 
52 0.390453125173 A 
53 0.719985040719 A 
54 0.977964675176 A 
55 1.54450254277 A 
56 2.14621503854 A 
57 2.99079642364 A 
58 3.39269707733 A 
59 3.33188837547 A 
60 4.10675880825 A 
61 6.96009219664 A 
62 9.04165938743 A 
63 8.65369320149 A 
64 7.94685353567 A 
65 5.99410112792 A 
66 4.270657622 A 
67 3.74053623603 A 
68 3.16701121242 A 
69 2.34745227622 A 
70 1.76409736552 A 
71 1.51200803675 A 
72 1.2907743594 A 
73 1.00681298597 A 
74 0.862744443537 A 
75 0.91574368888 A 
76 0.714689640717 A 
77 0.517175945403 A 
78 0.567676742354 A 
79 0.59107492188 A 
80 0.36357410485 A 
81 0.136113295885 A 
82 -0.0424484841936 A 
83 -0.0580144665363 A 
84 -0.0982479104419 A 
85 -0.125561965887 A 
86 -0.18724722966 A 
87 -0.319063282063 A 
88 -0.310923270725 A 
89 -0.297680012209 A 
90 -0.29067812137 A 
91 -0.153124902802 A 
92 -0.0832141989646 A 
93 0.0360608269851 A 
94 0.0692223913598 A 
95 0.0301088137407 A 
96 0.229967884645 A 
97 0.286834318788 A 
98 0.302023175627 A 
99 0.172030225713 A 
100 0.128331231506 A 
101 0.0852383292109 A 
102 -0.0890769934766 A 
103 -0.28596925454 A 
104 -0.277955689998 A 
105 -0.213135107915 A 
106 -0.187743795588 A 
107 -0.156312203071 A 
108 0.00927423989462 A 
109 0.0950491919392 A 
110 -0.103823712283 A 
111 -0.263438354304 A 
112 -0.169133590325 A 
113 -0.119342668528 A 
114 -0.184209907576 A 
115 -0.153083100597 A 
116 -0.118314865514 A 
117 -0.0218234673043 A 
118 0.0354090403385 A 
119 -0.176859459446 A 
120 -0.254330750514 A 
1 1.31156238699 B 
2 1.66603897664 B 
3 1.8595569523 B 
4 1.47610814343 B 
5 1.13938772251 B 
6 1.07959295698 B 
7 1.0562167754 B 
8 0.953732152873 B 
9 1.27923353158 B 
10 1.87416928486 B 
11 2.29643917738 B 
12 2.11874255833 B 
13 1.81800847267 B 
14 1.97156297894 B 
15 1.95639491025 B 
16 1.75903105961 B 
17 1.36979841803 B 
18 1.20025438569 B 
19 1.15465650184 B 
20 1.09201899355 B 
21 0.948241309108 B 
22 0.755764015696 B 
23 0.89321992313 B 
24 1.55401151175 B 
25 1.7724765184 B 
26 1.61741216053 B 
27 1.19119499499 B 
28 0.379190890768 B 
29 -0.280643671284 B 
30 -0.438517977457 B 
31 -0.358544058104 B 
32 -0.175439246148 B 
33 -0.152975829581 B 
34 -0.161103632796 B 
35 -0.174444281478 B 
36 0.0432634194416 B 
37 0.426620630846 B 
38 0.484334073737 B 
39 0.619581343298 B 
40 0.967283510405 B 
41 1.15176486771 B 
42 0.966602160933 B 
43 0.690373835041 B 
44 0.319762485659 B 
45 0.558607945261 B 
46 1.11704365618 B 
47 1.35119752184 B 
48 1.086453978 B 
49 0.522235623898 B 
50 0.331232373297 B 
51 0.470526554506 B 
52 0.88872478677 B 
53 1.3777468901 B 
54 1.98052619207 B 
55 2.74167480929 B 
56 3.71564209846 B 
57 4.7554986573 B 
58 5.35724571871 B 
59 5.09994377564 B 
60 6.79713731723 B 
61 13.5623123968 B 
62 19.9726094303 B 
63 20.6985773902 B 
64 19.5622430224 B 
65 16.9252890116 B 
66 13.785124688 B 
67 12.0153484193 B 
68 10.6335853944 B 
69 9.23145636242 B 
70 8.33279506304 B 
71 7.11679306668 B 
72 5.98971780649 B 
73 4.81795605529 B 
74 3.6240387853 B 
75 3.17710512841 B 
76 3.09525364338 B 
77 2.94968830182 B 
78 2.85812444624 B 
79 2.41084230435 B 
80 1.80196837641 B 
81 1.18822582466 B 
82 0.847087211338 B 
83 0.844579278397 B 
84 0.719435070951 B 
85 0.373826290695 B 
86 0.179833579104 B 
87 0.10827105313 B 
88 0.140513871238 B 
89 0.36900575791 B 
90 0.545788292614 B 
91 0.588906392532 B 
92 0.411607834074 B 
93 0.436297519059 B 
94 0.417543346098 B 
95 0.420644053229 B 
96 0.754192582582 B 
97 0.865901044214 B 
98 0.821331429891 B 
99 0.859522528975 B 
100 1.0698784309 B 
101 1.12094185211 B 
102 0.954696811999 B 
103 0.635033784692 B 
104 0.593828176146 B 
105 0.662067791202 B 
106 0.640073276401 B 
107 0.773737194106 B 
108 1.04778537143 B 
109 1.14218831145 B 
110 0.936124315428 B 
111 0.761897172562 B 
112 0.584860054282 B 
113 0.568945253284 B 
114 0.592650160898 B 
115 0.363421418416 B 
116 0.315516608971 B 
117 0.556218161647 B 
118 0.741402531046 B 
119 0.73670589581 B 
120 0.731201358535 B 
1 0.914487112088 B 
2 1.17888880951 B 
3 1.34882572489 B 
4 1.05705037522 B 
5 0.767924473683 B 
6 0.627155263031 B 
7 0.661419743127 B 
8 0.726639134719 B 
9 0.904404934323 B 
10 1.11446499538 B 
11 1.32234502189 B 
12 1.11272139974 B 
13 0.80278277695 B 
14 1.05206129918 B 
15 1.03054952945 B 
16 0.920053144065 B 
17 0.890783999963 B 
18 0.745241179888 B 
19 0.753375762718 B 
20 0.606204084282 B 
21 0.439550558806 B 
22 0.415665737741 B 
23 0.511097171088 B 
24 0.753958021098 B 
25 0.915744174748 B 
26 0.914912288237 B 
27 0.650537400908 B 
28 0.177843412682 B 
29 -0.182744261137 B 
30 -0.280968150367 B 
31 -0.131322561837 B 
32 -0.0936594361197 B 
33 -0.111213723334 B 
34 -0.0751949309223 B 
35 -0.114901791545 B 
36 -0.0165691620777 B 
37 0.117705450621 B 
38 0.195665130311 B 
39 0.49300993106 B 
40 0.748293222013 B 
41 0.702261888166 B 
42 0.579761929719 B 
43 0.354296503405 B 
44 0.0685749425124 B 
45 0.276465165244 B 
46 0.833851789425 B 
47 0.952399770341 B 
48 0.780124651512 B 
49 0.389046185042 B 
50 0.240762613037 B 
51 0.334216612367 B 
52 0.497505803488 B 
53 0.759900678942 B 
54 1.12736521148 B 
55 1.77820644505 B 
56 2.60137514 B 
57 3.11618984654 B 
58 3.21453966104 B 
59 3.02507885677 B 
60 4.10630457704 B 
61 7.81645787291 B 
62 11.474225964 B 
63 12.4863009071 B 
64 11.5994621204 B 
65 9.5999931249 B 
66 7.96585566708 B 
67 7.08309536929 B 
68 6.04261032076 B 
69 5.26284702902 B 
70 4.76880466452 B 
71 4.10897764688 B 
72 3.33692117069 B 
73 2.6513184514 B 
74 2.25667303445 B 
75 1.83839013124 B 
76 1.84439486988 B 
77 1.74545691393 B 
78 1.60528910561 B 
79 1.42843608445 B 
80 0.854469270873 B 
81 0.563227776699 B 
82 0.299704948636 B 
83 0.270143019019 B 
84 0.283668987216 B 
85 0.181017474033 B 
86 0.0822636124446 B 
87 -0.0465301247043 B 
88 -0.000460798489744 B 
89 0.0926334491843 B 
90 0.192295768771 B 
91 0.29542265617 B 
92 0.218214141112 B 
93 0.145843998014 B 
94 0.12500365606 B 
95 0.147889577395 B 
96 0.368717140352 B 
97 0.580075802767 B 
98 0.459540843701 B 
99 0.459168312255 B 
100 0.614213389976 B 
101 0.627367541442 B 
102 0.562408018057 B 
103 0.31716603245 B 
104 0.288874098133 B 
105 0.303797627692 B 
106 0.338691064084 B 
107 0.336034553249 B 
108 0.587964074115 B 
109 0.649227026019 B 
110 0.541946830382 B 
111 0.542082081996 B 
112 0.51192491824 B 
113 0.327474693143 B 
114 0.254878532604 B 
115 0.134544321919 B 
116 0.100368014222 B 
117 0.211272916527 B 
118 0.267339751552 B 
119 0.30990753715 B 
120 0.444492582364 B 

Cảm ơn một lần nữa!

Answer 1

Như @MrFlick đã nói, bạn không thể tính toán lỗi chuẩn cho từng giá trị x. Tuy nhiên, có một số tùy chọn bạn có thể xem xét.

Lựa chọn 1: âm mưu một hoàng thổ trơn tru với một khoảng thời gian rất nhỏ với stat_smooth trong đó bạn có thể bao gồm một khu vực bóng mờ cho sai số chuẩn:

ggplot(dat, aes(x=pos,y=value, colour=type)) + 
    stat_smooth(method="loess", span=0.1, se=TRUE, aes(fill=type), alpha=0.3) + 
    theme_bw() 

này cung cấp cho:

Tùy chọn 2: vì bạn có giá trị cao và thấp cho mỗi giá trị x, bạn có thể vẽ các đường riêng biệt cho các giá trị cao và thấp. Bạn cần phải tạo một cao/biến thấp đầu tiên:

dat$level <- rep(c("high","low"), each=120) 
ggplot(dat, aes(x=pos,y=value, colour=type)) + 
    geom_line(aes(linetype=level)) + 
    theme_bw() 

này cung cấp cho:

Lựa chọn 3: như bạn có một cao và một giá trị thấp cho mỗi giá trị x, bạn có thể vẽ một geom_ribbon lệch giữa giá trị cao và thấp với:

ggplot(dat, aes(x=pos,y=value, colour=type)) + 
    stat_summary(geom="ribbon", fun.ymin="min", fun.ymax="max", aes(fill=type), alpha=0.3) + 
    theme_bw() 

này cung cấp cho: