對僅位於特定時間間隔內的值執行算術表達式？

我有包含這塊數據對僅位於特定時間間隔內的值執行算術表達式？

  EUR.CLOSE 
2014-08-28 1.3182 
2014-08-29 1.3132 
2014-09-01 1.3128 
2014-09-02 1.3133 
2014-09-03 1.3150 
2014-09-04 1.2944 
2014-09-05 1.2951 
2014-09-08 1.2895 
2014-09-09 1.2937 
2014-09-10 1.2917

的我具有被基於一定的信號來計算行間隔data.frames的列表。在這種情況下，假設計算的行間隔是rowintv <- c(5,10,17,22)。我用下面的函數來獲取基於行間隔的最大收盤價：

sapply(seq_along(rowintv), function(x) max(data[findInterval(seq_along(data), rowintv, left.open = TRUE) == (x - 1)]))

這將返回相應的最大值[1] 1.3182 1.2951 1.2963 1.2849。但是，現在我想在算術表達式中使用這些最大值，並使用與子區間相匹配的適當收盤價。舉例來說，我想：

   EUR.CLOSE 
2014-08-28 1.3182 - 3*1.3182 
2014-08-29 1.3132 - 3* 1.3182 
2014-09-01 1.3128 - 3* 1.3182 
2014-09-02 1.3133 - 3* 1.3182 
2014-09-03 1.3150 - 3* 1.3182 (this is 5th row) 
2014-09-04 1.2944 - 3 * 1.2951 (for rows 6-10 we use maximum value 1.2951)

我試着

sapply(seq_along(sig.intv), function(y) newtrendsig[[x]][findInterval(seq_along(newtrendsig[[x]][,4]), sig.intv, left.open = TRUE) == (y * newtrendsig[[x]][,3] - max.val),4])

這樣做，但這種返回警告說In y * newtrendsig[[x]][, 3] - max.val : longer object length is not a multiple of shorter object length

附件是我的原始數據的樣本的dput。收盤價格可以通過data[[x]][,4]獲得。

structure(list(EUR.20D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), EUR.CLOSE = c(-1, 
-1, -1, -1, -1, -1, -1, -1, -1, -1), EUR.20D.1 = c(0, 0, 0, 0, 
0, 0, 0, 0, 0, 0), EUR.CLOSE.1 = c(1.0643, 1.0598, 1.0578, 1.0601, 
1.0674, 1.0616, 1.0614, 1.0536, 1.0558, 1.0582), EUR.20D.2 = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("MA crossover", 
"Price break"), class = "factor"), atr...2. = c(0.00917523899027, 
0.00921272191953643, 0.00911895606814097, 0.00893903063470233, 
0.00997195701793786, 0.00953110294522802, 0.00904316702056887, 
0.00858294080481395, 0.00842701646161295, 0.00826080100006917 
), EUR.CLOSE.2 = c(-0.607022786701527, -1.02726933134104, -1.15866193234909, 
-0.925233644859815, -0.252312867956279, -0.7479431563201, -0.701655907942751, 
-1.33907669257421, -1.04039741306588, -0.768942235558888), EUR.CLOSE.3 = c(0.377251721210978, 
-0.00943485234455977, -0.179296027177504, 0.0660751368699401, 
0.745634733364796, 0.18875047187618, 0.179329872581408, -0.547479705493657, 
-0.339814989616748, -0.141549495140139), EUR.CLOSE.4 = c(-0.0011268664916733, 
-0.00423709498833686, -0.00188893142678216, 0.00217196364717242, 
0.00686254162079234, -0.00544858088184653, -0.000188412624203348, 
-0.00737591996472312, 0.00208590196044455, 0.00227057808051545 
)), .Names = c("EUR.20D", "EUR.CLOSE", "EUR.20D.1", "EUR.CLOSE.1", 
"EUR.20D.2", "atr...2.", "EUR.CLOSE.2", "EUR.CLOSE.3", "EUR.CLOSE.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame") 
structure(list(JPY.20D = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, 
-1), JPY.CLOSE = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1), JPY.20D.1 = c(-1, 
-1, -1, -1, -1, -1, -1, -1, -1, -1), JPY.CLOSE.1 = c(113.22, 
113.74, 114.26, 114.16, 113.24, 112.84, 113.1, 113.68, 113.31, 
112.61), JPY.20D.2 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), .Label = c("MA crossover", "Price break"), class = "factor"), 
    atr...2. = c(0.825994754458168, 0.804137986282584, 0.831699558690971, 
    0.845149590213044, 0.828353190912112, 0.809899391561248, 
    0.817049435021158, 0.779403046805361, 0.755874257747835, 
    0.727597525051561), JPY.CLOSE.2 = c(-0.16753372718455, 0.317516316810725, 
    0.705094306363486, 0.634696755994357, -0.105857445306991, 
    -0.379623907477702, -0.167711183687891, 0.353107344632773, 
    0.0176538088092471, -0.512412757310715), JPY.CLOSE.3 = c(-1.65899418049162, 
    -1.20733084339442, -0.755667506297221, -0.851137745353486, 
    -1.6330785267547, -1.93795081254887, -1.68636995827539, -1.15642118076689, 
    -1.40955364134691, -1.92475178540323), JPY.CLOSE.4 = c(-0.000264935754629825, 
    0.00458231327013969, 0.00456141141766331, -0.000875580127735809, 
    -0.00809151292488242, -0.00353857410990255, 0.00230149698827908, 
    0.00511510066677001, -0.00326005839636956, -0.00619690368354142 
    )), .Names = c("JPY.20D", "JPY.CLOSE", "JPY.20D.1", "JPY.CLOSE.1", 
"JPY.20D.2", "atr...2.", "JPY.CLOSE.2", "JPY.CLOSE.3", "JPY.CLOSE.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame") 
structure(list(GBP.20D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), GBP.CLOSE = c(-1, 
-1, -1, -1, -1, -1, -1, -1, -1, -1), GBP.20D.1 = c(0, 0, 0, 0, 
0, 0, 0, 0, 0, 0), GBP.CLOSE.1 = c(1.2491, 1.2526, 1.2468, 1.2461, 
1.2489, 1.2412, 1.2463, 1.2473, 1.245, 1.2556), GBP.20D.2 = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("MA crossover", 
"Price break"), class = "factor"), atr...2. = c(0.0117578295696, 
0.0116108417432, 0.0117386387615428, 0.0119501645642898, 0.0120680099525548, 
0.0116131520988009, 0.0118336412346008, 0.0114026668607008, 0.0109524763706507, 
0.0105058709156042), GBP.CLOSE.2 = c(0.120230843218967, 0.207999999999995, 
-0.279932816124135, -0.41556780947815, -0.247603833865823, -0.878453921098858, 
-0.439367311072061, -0.3435602428891, -0.455744782921549, 0.407836865253907 
), GBP.CLOSE.3 = c(0.563561710007237, 0.877828783119909, 0.451176281018355, 
0.419050689016044, 0.660917224147657, 0.0644953240890144, 0.50806451612903, 
0.621168118747986, 0.451831531386159, 1.29073894804776), GBP.CLOSE.4 = c(-0.00048023051987453, 
0.00279809911944895, -0.00464112219813048, -0.000561594944360089, 
0.0022444899202175, -0.00618451029481418, 0.00410050825810596, 
0.000802053299332334, -0.00184568523285542, 0.00847801606899046 
)), .Names = c("GBP.20D", "GBP.CLOSE", "GBP.20D.1", "GBP.CLOSE.1", 
"GBP.20D.2", "atr...2.", "GBP.CLOSE.2", "GBP.CLOSE.3", "GBP.CLOSE.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame") 
structure(list(CHF.CLOSE = c(-1, -1, -1, -1, -1, -1, -1, -1, 
-1, -1), CHF.OPEN = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1), 
    CHF.CLOSE.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1), 
    CHF.OPEN.1 = c(1.0024, 1.0057, 1.0062, 1.0055, 0.9971, 1.0026, 
    1.0028, 1.0097, 1.0103, 1.0063), CHF.CLOSE.2 = structure(c(1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("MA crossover", 
    "Price break"), class = "factor"), atr...2. = c(0.00728057182205798, 
    0.00722481669191098, 0.00708732978534591, 0.00693109194353549, 
    0.00752887109042581, 0.00716966601253826, 0.00682897558307124, 
    0.00649119161285187, 0.0063489636405053, 0.00615260909475493 
    ), CHF.OPEN.2 = c(0.360432519022821, 0.721081622433649, 0.75097626914989, 
    0.690967354296016, -0.110198357042676, 0.440793428170703, 
    0.430645968953416, 1.07107107107108, 1.08054027013506, 0.650130026005196 
    ), CHF.OPEN.3 = c(-0.870253164556976, -0.543908227848107, 
    -0.484620710117706, -0.553852240134512, -1.34560205797961, 
    -0.771971496437058, -0.732528212235208, -0.049495149475346, 
    0.0297029702970264, -0.316988608221901), CHF.OPEN.4 = c(0.000698567964139939, 
    0.00328669186857626, 0.00049704260678339, -0.000695928844511353, 
    -0.00838914337795957, 0.00550083899465574, 0.000199461454735274, 
    0.00685716972613716, 0.000594059423411153, -0.00396707849439904 
    )), .Names = c("CHF.CLOSE", "CHF.OPEN", "CHF.CLOSE.1", "CHF.OPEN.1", 
"CHF.CLOSE.2", "atr...2.", "CHF.OPEN.2", "CHF.OPEN.3", "CHF.OPEN.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame") 
structure(list(AUD.20D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), AUD.CLOSE = c(-1, 
-1, -1, -1, -1, -1, -1, -1, -1, -1), AUD.20D.1 = c(0, 0, 0, 0, 
0, 0, 0, 0, 0, 0), AUD.CLOSE.1 = c(0.7674, 0.764, 0.7663, 0.771, 
0.7694, 0.7664, 0.7688, 0.7675, 0.7703, 0.7715), AUD.20D.2 = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("MA crossover", 
"Price break"), class = "factor"), atr...2. = c(0.0100596741007665, 
0.0100625545221403, 0.0100438006277017, 0.00981924344000875, 
0.00956786890857955, 0.0095130211293953, 0.00932637676300992, 
0.00889592127993779, 0.00850335547422795, 0.00819597294035453 
), AUD.CLOSE.2 = c(1.12004216629331, 0.566012899828876, 0.802420415680083, 
1.28744088281661, 0.984381152382196, 0.511475409836068, 0.760157273918745, 
0.537070998166098, 0.811412118832611, 0.849673202614373), AUD.CLOSE.3 = c(3.21452589105581, 
2.7019760720527, 2.95579739352412, 3.53162347253928, 3.24745034889962, 
2.78969957081544, 3.05630026809652, 2.82690246516613, 3.1329495247021, 
3.18309482412731), AUD.CLOSE.4 = c(0.00640566933128534, -0.00444038864633145, 
0.00300594880983807, 0.0061146355869709, -0.00207738324513479, 
-0.00390676366154397, 0.00312663099943206, -0.00169237819473061, 
0.00364156989756792, 0.00155662244429539)), .Names = c("AUD.20D", 
"AUD.CLOSE", "AUD.20D.1", "AUD.CLOSE.1", "AUD.20D.2", "atr...2.", 
"AUD.CLOSE.2", "AUD.CLOSE.3", "AUD.CLOSE.4"), na.action = structure(1:19, .Names = c("2014-08-28", 
"2014-08-29", "2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", 
"2014-09-05", "2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", 
"2014-09-12", "2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", 
"2014-09-19", "2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame") 
structure(list(CAD.20D = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, 
-1), CAD.CLOSE = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1), CAD.20D.1 = c(-1, 
-1, -1, -1, -1, -1, -1, -1, -1, -1), CAD.CLOSE.1 = c(1.3083, 
1.3071, 1.3076, 1.308, 1.3071, 1.3096, 1.3106, 1.3141, 1.3164, 
1.3105), CAD.20D.2 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), .Label = "MA crossover", class = "factor"), atr...2. = c(0.00897996644549454, 
0.00881711169938778, 0.0089516037208601, 0.00875506059794152, 
0.00876541341237426, 0.00865359816863325, 0.00852119829944516, 
0.00806254127805621, 0.00797235975819507, 0.007631476918324), 
    CAD.CLOSE.2 = c(-0.403471376370286, -0.456933973040896, -0.434021168049953, 
    -0.327668978129999, -0.30508733124857, -0.0305343511450348, 
    0.0992896967845474, 0.374274366025063, 0.511567534549908, 
    0.0534432737822509), CAD.CLOSE.3 = c(-1.24547101449275, -1.30625188764724, 
    -1.23867069486406, -1.18606935106142, -1.23913864752552, 
    -1.03529056147509, -0.952237001209186, -0.695231617924875, 
    -0.498866213151923, -0.914864660517163), CAD.CLOSE.4 = c(-0.00472778065310547, 
    -0.000917641725324381, 0.000382453058549392, 0.000305857167088586, 
    -0.000688310225637978, 0.00191080426541917, 0.000763300548471235, 
    0.00266697304419594, 0.00174871741959248, -0.00449199430572389 
    )), .Names = c("CAD.20D", "CAD.CLOSE", "CAD.20D.1", "CAD.CLOSE.1", 
"CAD.20D.2", "atr...2.", "CAD.CLOSE.2", "CAD.CLOSE.3", "CAD.CLOSE.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame")

來源

2017-03-23 Nikitau

你可能需要的東西是這樣的：

res <- sapply(seq_along(sig.intv), function(x) { 
data[findInterval(seq_along(data), rowintv, left.open = TRUE) == (x - 1)] - 3 * sig.intv[x] 
} 
) 
res <- ts(unlist(res)) 
res 
Time Series: 
Start = 1 
End = 22 
Frequency = 1 
[1] -2.6364 -2.6414 -2.6418 -2.6413 -2.6396 -2.5909 -2.5902 -2.5958 -2.5916 -2.5936 -2.5964 -2.5926 -2.5949 -2.5929 
[15] -2.6024 -2.5966 -2.6060 -2.5698 -2.5700 -2.5767 -2.5796 -2.5863

而且，你的第一個sapply可能需要

1:(length(rowintv)+1)

的第一個參數，可以跨越所有間隔。

編輯：我猜你的意思是，你的數據是這樣的：

D <- list(structure(list(EUR.20D = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), 
EUR.CLOSE = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1), EUR.20D.1 = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0), EUR.CLOSE.1 = c(1.0643, 1.0598, 
1.0578, 1.0601, 1.0674, 1.0616, 1.0614, 1.0536, 1.0558, 1.0582 
), EUR.20D.2 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L), .Label = c("MA crossover", "Price break"), class = "factor"), 
atr...2. = c(0.00917523899027, 0.00921272191953643, 0.00911895606814097, 
0.00893903063470233, 0.00997195701793786, 0.00953110294522802, 
0.00904316702056887, 0.00858294080481395, 0.00842701646161295, 
0.00826080100006917), EUR.CLOSE.2 = c(-0.607022786701527, 
-1.02726933134104, -1.15866193234909, -0.925233644859815, 
-0.252312867956279, -0.7479431563201, -0.701655907942751, 
-1.33907669257421, -1.04039741306588, -0.768942235558888), 
EUR.CLOSE.3 = c(0.377251721210978, -0.00943485234455977, 
-0.179296027177504, 0.0660751368699401, 0.745634733364796, 
0.18875047187618, 0.179329872581408, -0.547479705493657, 
-0.339814989616748, -0.141549495140139), EUR.CLOSE.4 = c(-0.0011268664916733, 
-0.00423709498833686, -0.00188893142678216, 0.00217196364717242, 
0.00686254162079234, -0.00544858088184653, -0.000188412624203348, 
-0.00737591996472312, 0.00208590196044455, 0.00227057808051545 
)), .Names = c("EUR.20D", "EUR.CLOSE", "EUR.20D.1", "EUR.CLOSE.1", 
"EUR.20D.2", "atr...2.", "EUR.CLOSE.2", "EUR.CLOSE.3", "EUR.CLOSE.4" 
), na.action = structure(1:19, .Names = c("2014-08-28", "2014-08-29", 
"2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", "2014-09-05", 
"2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", "2014-09-12", 
"2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", "2014-09-19", 
"2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"), 
structure(list(JPY.20D = c(-1, -1, -1, -1, -1, -1, -1, -1, 
-1, -1), JPY.CLOSE = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, 
-1), JPY.20D.1 = c(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1 
), JPY.CLOSE.1 = c(113.22, 113.74, 114.26, 114.16, 113.24, 
112.84, 113.1, 113.68, 113.31, 112.61), JPY.20D.2 = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("MA crossover", 
"Price break"), class = "factor"), atr...2. = c(0.825994754458168, 
0.804137986282584, 0.831699558690971, 0.845149590213044, 
0.828353190912112, 0.809899391561248, 0.817049435021158, 
0.779403046805361, 0.755874257747835, 0.727597525051561), 
    JPY.CLOSE.2 = c(-0.16753372718455, 0.317516316810725, 
    0.705094306363486, 0.634696755994357, -0.105857445306991, 
    -0.379623907477702, -0.167711183687891, 0.353107344632773, 
    0.0176538088092471, -0.512412757310715), JPY.CLOSE.3 = c(-1.65899418049162, 
    -1.20733084339442, -0.755667506297221, -0.851137745353486, 
    -1.6330785267547, -1.93795081254887, -1.68636995827539, 
    -1.15642118076689, -1.40955364134691, -1.92475178540323 
    ), JPY.CLOSE.4 = c(-0.000264935754629825, 0.00458231327013969, 
    0.00456141141766331, -0.000875580127735809, -0.00809151292488242, 
    -0.00353857410990255, 0.00230149698827908, 0.00511510066677001, 
    -0.00326005839636956, -0.00619690368354142)), .Names = c("JPY.20D", 
"JPY.CLOSE", "JPY.20D.1", "JPY.CLOSE.1", "JPY.20D.2", "atr...2.", 
"JPY.CLOSE.2", "JPY.CLOSE.3", "JPY.CLOSE.4"), na.action = structure(1:19, .Names = c("2014-08-28", 
"2014-08-29", "2014-09-01", "2014-09-02", "2014-09-03", "2014-09-04", 
"2014-09-05", "2014-09-08", "2014-09-09", "2014-09-10", "2014-09-11", 
"2014-09-12", "2014-09-15", "2014-09-16", "2014-09-17", "2014-09-18", 
"2014-09-19", "2014-09-22", "2014-09-23"), class = "omit"), row.names = c("2017-02-10", 
"2017-02-13", "2017-02-14", "2017-02-15", "2017-02-16", "2017-02-17", 
"2017-02-20", "2017-02-21", "2017-02-22", "2017-02-23"), class = "data.frame"))

這個數據該代碼應工作：

rowintv <- c(5,10) 
get_int_max <- function(DF, rowintv) { 
    sapply(seq_along(rowintv), function(x) 
max(DF[findInterval(seq_along(DF), rowintv, left.open = TRUE) == (x - 1), 4]) 
)} 
int_max_list <- lapply(D, function(x) get_int_max(x, rowintv)) 

substract <- function(DF, int_max, rowintv) { 
    s <- sapply(seq_along(rowintv), function(x) { 
v <- 
    DF[findInterval(seq_along(DF), rowintv, left.open = TRUE) == (x - 1), 4] - 
    3 * int_max[[x]] 
return(v) 
    }) 
    unlist(s) 
} 

lapply(1:length(D), function(x) substract(D[[x]], int_max_list[[x]], rowintv))

附：在我看來你的數據結構有點複雜，所以我建議從這個列表創建一個data.frame

來源

2017-03-23 16:02:51 minem

謝謝。我嘗試使用'res < - sapply（seq_along（sig.intv），function（x）sig.intv < - which（newtrendsig [[x]] [，]）爲我的原始數據（數據框列表） 3]！= lag（newtrendsig [[x]] [，3]）） newtrendsig [[x]] [findInterval（seq_along（newtrendsig [[x]] [，4]），sig.intv，left.open = TRUE）==（x-1），4] - 3 * sig.intv [x] } ）其中'newtrendsig [[x]] [，4]'對應於收盤價，但我得到一個下標的bounsd錯誤。我會在原始文章中附上我的原始數據樣本。 – Nikitau

@Nikitau我編輯了我的答案，你可能沒有收到通知 – minem

對僅位於特定時間間隔內的值執行算術表達式？

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