r - 如何绘制时间 cdf？

Question

我有以下值:

Day 1: X11 X12 X13 X14 X15 ...
Day 2: X21 X22 X23 X24 X25 ...
Day 3: X31 X32 X33 X34 X35 ...
...
...

我可以使用每天的值来绘制不同的 CDF，但有没有一种方法可以可视化所有天的 CDF，以查看分布如何随时间变化？是否有类似 3D 变体的东西可供我绘制？

实际值:

structure(list(Time = structure(c(1354348800, 1354435200, 1354521600, 
1354608000, 1354694400, 1354780800, 1354867200, 1354953600, 1355040000, 
1355126400, 1355212800, 1355299200, 1355385600, 1355472000, 1355558400, 
1355644800, 1355731200, 1355817600, 1355904000, 1355990400, 1356076800, 
1356163200, 1356249600, 1356336000, 1356422400, 1356508800, 1356595200, 
1356681600, 1356768000, 1356854400, 1356940800, 1354348800, 1354435200, 
1354521600, 1354608000, 1354694400, 1354780800, 1354867200, 1354953600, 
1355040000, 1355126400, 1355212800, 1355299200, 1355385600, 1355472000, 
1355558400, 1355644800, 1355731200, 1355817600, 1355904000, 1355990400, 
1356076800, 1356163200, 1356249600, 1356336000, 1356422400, 1356508800, 
1356595200, 1356681600, 1356768000, 1356854400, 1356940800, 1354348800, 
1354435200, 1354521600, 1354608000, 1354694400, 1354780800, 1354867200, 
1354953600, 1355040000, 1355126400, 1355212800, 1355299200, 1355385600, 
1355472000, 1355558400, 1355644800, 1355731200, 1355817600, 1355904000, 
1355990400, 1356076800, 1356163200, 1356249600, 1356336000, 1356422400, 
1356508800, 1356595200, 1356681600, 1356768000, 1356854400, 1356940800, 
1354348800, 1354435200, 1354521600, 1354608000, 1354694400, 1354780800, 
1354867200, 1354953600, 1355040000, 1355126400, 1355212800, 1355299200, 
1355385600, 1355472000, 1355558400, 1355644800, 1355731200, 1355817600, 
1355904000, 1355990400, 1356076800, 1356163200, 1356249600, 1356336000, 
1356422400, 1356508800, 1356595200, 1356681600, 1356768000, 1356854400, 
1356940800, 1354348800, 1354435200, 1354521600, 1354608000, 1354694400, 
1354780800, 1354867200, 1354953600, 1355040000, 1355126400, 1355212800, 
1355299200, 1355385600, 1355472000, 1355558400, 1355644800, 1355731200, 
1355817600, 1355904000, 1355990400, 1356076800, 1356163200, 1356249600, 
1356336000, 1356422400, 1356508800, 1356595200, 1356681600, 1356768000, 
1356854400, 1356940800, 1354348800, 1354435200, 1354521600, 1354608000, 
1354694400, 1354780800, 1354867200, 1354953600, 1355040000, 1355126400, 
1355212800, 1355299200, 1355385600, 1355472000, 1355558400, 1355644800, 
1355731200, 1355817600, 1355904000, 1355990400, 1356076800, 1356163200, 
1356249600, 1356336000, 1356422400, 1356508800, 1356595200, 1356681600, 
1356768000, 1356854400, 1356940800), class = c("POSIXct", "POSIXt"
), tzone = ""), Value = c(430664.239261698, 490234.194921927, 
526998.520971122, 536602.462982633, 258691.669906957, 11829.8290116318, 
12650.9461086689, 2720.1227453922, 6148.95630258592, 2680.86993550808, 
2678.03258008561, 2665.03710105507, 2704.83781604574, 2704.99305811391, 
2742.7040489269, 2802.16126409598, 2835.37392203882, 2822.02107441536, 
2816.32800725421, 2798.97376034702, 2796.01930330326, 2754.58930695667, 
2745.58482436398, 2729.8646537471, 2706.30089379909, 2657.97901504968, 
2755.8939918735, 2756.32635948648, 2703.73644754399, 2595.09862261747, 
2583.96164402217, 1103.38595759987, 1410.11179619836, 4758.52642632149, 
4799.73333750023, 3881.64395298922, 2769.52071665839, 2777.36511823707, 
2728.37598724549, 2732.36209370411, 2695.9513678436, 2686.83499265917, 
2681.5743717285, 2720.45290857566, 2732.73841594837, 2760.53934947503, 
2811.42766223853, 2844.41105991693, 2825.55269421361, 2820.7691523964, 
2807.55312109634, 2804.11955879203, 2757.32663905538, 2745.86930679521, 
2739.23425025641, 2715.98260303707, 2692.68857278371, 3527.71521116871, 
4262.25327731706, 4533.9804534, 4481.65508241964, 4421.37186792114, 
19613453.922832, 124804222.41819, 141787648.586654, 130924910.79881, 
168814882.872211, 11894959.6456705, 8774239.566537, 16080698.3234849, 
17161993.52566, 22336448.9385156, 15252276.6007502, 10331573.337916, 
8976597.77324162, 17169136.7951364, 12183504.3046438, 6957562.92857611, 
12930867.2067763, 10663528.8499475, 8969032.06072141, 12857780.0335602, 
10766886.886599, 14795620.653363, 9825272.66156014, 11044813.0699568, 
10367171.6540806, 9610185.60847421, 10931660.4285495, 8394075.58812457, 
8993089.38056002, 8026650.35585018, 7946595.12661373, 114329906.004844, 
137475638.687273, 148815385.289035, 135307862.23453, 184737114.110537, 
119730959.539068, 69757385.6095225, 90614972.0916845, 86831718.3941103, 
119775130.022637, 88442212.7020717, 58451067.337829, 65388376.2367906, 
63443348.7417144, 57280954.523376, 45166897.0970657, 83554097.8501678, 
66201693.7873501, 70795197.9863679, 84221546.3400137, 72983744.7919536, 
79897785.2230573, 69847018.9176478, 73346675.6554418, 64914201.3793851, 
63947528.2287373, 65351437.5297966, 59076239.7375999, 42688084.2661814, 
42066287.169797, 39734565.1701957, 90506964.9337797, 100149152.452364, 
120257643.646244, 111528999.398328, 138621214.049053, 9371.8136697, 
56524340.9066957, 73183012.7386646, 73134499.5072141, 91844218.5996012, 
59462704.401716, 46340856.9647138, 49809994.4841905, 52046927.2065564, 
43534299.417627, 37959416.2194319, 64876408.0181902, 55169784.3656278, 
55637721.2148036, 64303390.999086, 55469744.4302739, 59472270.8402672, 
52495047.7346662, 59934890.0182395, 57773465.6418628, 57227960.3434529, 
58180354.3542921, 50719237.2638962, 33168848.2017861, 33850765.333152, 
33841026.2326982, 110504056.059923, 133797335.531811, 148626502.57032, 
130569007.27317, 163603482.922618, 110945447.425452, 67150219.14672, 
85584433.1881761, 76873561.2170393, 117860559.12102, 84629012.3662336, 
54204572.2980234, 58898821.9609343, 62180038.7679437, 53059333.3332883, 
43914570.1205393, 79475697.2825237, 64196704.372024, 66182175.1487631, 
80851142.6092836, 65475805.206847, 68931230.2593625, 59859872.3417313, 
65228418.926433, 61498299.9737327, 60767088.8695188, 62752189.9148476, 
56770234.222601, 40910036.2385198, 39235601.7774785, 37635952.1705463
)), .Names = c("Time", "Value"), row.names = c(NA, -186L), class = "data.frame")

编辑:结果图像

Answer 1

当然。检查包 rgl 中的函数 rgl.surface():

library(rgl)
data <- lapply(seq(0,2,by=0.1),function(i){rnorm(100)+i})  # a list with example data vectors
m <- sapply(data,function(i){ecdf(i)(seq(-3,5,by=0.1))})   # a matrix with the empirical CDF for each vector in the list, over a given range -3 to 5
rgl.surface(1:nrow(m), 5*(1:ncol(m)), m*20)    # play with the coefficients to get a better result

您甚至可以旋转这个表面!更多信息，查看this question .

更新:以下是您可以对数据执行的操作:

values.per.day <- lapply(unique(data$Time), function(x)data$Value[data$Time==x])
m <- sapply(values.per.day, function(x) ecdf(x)(seq(min(data$Value), max(data$Value), length.out=1000)) )
rgl.surface(1:nrow(m), 5*(1:ncol(m)), m*20)