R Under development (unstable) (2022-04-08 r82135) -- "Unsuffered Consequences"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> pkgname <- "fts"
> source(file.path(R.home("share"), "R", "examples-header.R"))
> options(warn = 1)
> library('fts')
Loading required package: zoo

Attaching package: ‘zoo’

The following objects are masked from ‘package:base’:

    as.Date, as.Date.numeric

> 
> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
> base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
> cleanEx()
> nameEx("any.all.fts")
> ### * any.all.fts
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fts.logical
> ### Title: Logical subsets of objects
> ### Aliases: fts.logical col.any col.all row.any row.all
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(seq(from=Sys.Date(),by="months",length.out=50),matrix(rnorm(100),nrow=50))
> jj <- x > 0
> row.all(jj)
2022-04-11 2022-05-11 2022-06-11 2022-07-11 2022-08-11 2022-09-11 2022-10-11 
     FALSE      FALSE      FALSE      FALSE       TRUE      FALSE      FALSE 
2022-11-11 2022-12-11 2023-01-11 2023-02-11 2023-03-11 2023-04-11 2023-05-11 
     FALSE       TRUE      FALSE       TRUE      FALSE      FALSE      FALSE 
2023-06-11 2023-07-11 2023-08-11 2023-09-11 2023-10-11 2023-11-11 2023-12-11 
     FALSE      FALSE      FALSE       TRUE       TRUE       TRUE       TRUE 
2024-01-11 2024-02-11 2024-03-11 2024-04-11 2024-05-11 2024-06-11 2024-07-11 
     FALSE       TRUE      FALSE      FALSE      FALSE      FALSE      FALSE 
2024-08-11 2024-09-11 2024-10-11 2024-11-11 2024-12-11 2025-01-11 2025-02-11 
     FALSE      FALSE      FALSE      FALSE       TRUE      FALSE      FALSE 
2025-03-11 2025-04-11 2025-05-11 2025-06-11 2025-07-11 2025-08-11 2025-09-11 
     FALSE      FALSE      FALSE       TRUE       TRUE      FALSE      FALSE 
2025-10-11 2025-11-11 2025-12-11 2026-01-11 2026-02-11 2026-03-11 2026-04-11 
      TRUE       TRUE      FALSE      FALSE      FALSE      FALSE      FALSE 
2026-05-11 
     FALSE 
> row.any(jj)
2022-04-11 2022-05-11 2022-06-11 2022-07-11 2022-08-11 2022-09-11 2022-10-11 
      TRUE       TRUE       TRUE       TRUE       TRUE       TRUE       TRUE 
2022-11-11 2022-12-11 2023-01-11 2023-02-11 2023-03-11 2023-04-11 2023-05-11 
      TRUE       TRUE      FALSE       TRUE       TRUE       TRUE       TRUE 
2023-06-11 2023-07-11 2023-08-11 2023-09-11 2023-10-11 2023-11-11 2023-12-11 
      TRUE       TRUE      FALSE       TRUE       TRUE       TRUE       TRUE 
2024-01-11 2024-02-11 2024-03-11 2024-04-11 2024-05-11 2024-06-11 2024-07-11 
      TRUE       TRUE      FALSE       TRUE       TRUE      FALSE       TRUE 
2024-08-11 2024-09-11 2024-10-11 2024-11-11 2024-12-11 2025-01-11 2025-02-11 
      TRUE       TRUE       TRUE      FALSE       TRUE      FALSE       TRUE 
2025-03-11 2025-04-11 2025-05-11 2025-06-11 2025-07-11 2025-08-11 2025-09-11 
      TRUE       TRUE      FALSE       TRUE       TRUE      FALSE       TRUE 
2025-10-11 2025-11-11 2025-12-11 2026-01-11 2026-02-11 2026-03-11 2026-04-11 
      TRUE       TRUE       TRUE       TRUE       TRUE       TRUE      FALSE 
2026-05-11 
      TRUE 
> 
> col.any(x > 0)
[1] TRUE TRUE
> col.all(x > -3)
[1] TRUE TRUE
> 
> 
> 
> cleanEx()
> nameEx("apply")
> ### * apply
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: apply
> ### Title: Apply Function
> ### Aliases: apply row.apply column.apply
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="months",length.out=24),data=1:24)
> y <- fts(index=seq(from=Sys.Date(),by="months",length.out=24),data=1:24)
> 
> z <- cbind(x,y)
> 
> ## returns vector
> z.col.sum <- column.apply(z,sum)
> 
> ## returns fts
> z.row.sum <- row.apply(z,sum)
> 
> 
> 
> 
> cleanEx()
> nameEx("as.fts")
> ### * as.fts
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: as.fts
> ### Title: Convert from/to fts
> ### Aliases: as.fts as.fts.default as.fts.data.frame as.fts.matrix
> ###   as.fts.zoo as.data.frame.fts as.matrix.fts
> ### Keywords: ts
> 
> ### ** Examples
> 
> N <- 100
> xm <- matrix(rnorm(N))
> dts <- format(seq(from=Sys.Date(),length.out=N,by="days"),"%Y-%m-%d")
> rownames(xm) <- dts
> x.from.m <- as.fts(xm)
> x.from.df <- as.fts(data.frame(asofdate=dts,my.data=xm))
> 
> 
> 
> cleanEx()
> nameEx("event.dates")
> ### * event.dates
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: event.dates
> ### Title: Extract Dates
> ### Aliases: event.dates
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=rnorm(100))
> x.bool <- x > 10
> event.dates(x.bool)
Date of length 0
> 
> ## ignores NA's
> x.bool[10:20] <- NA
> event.dates(x.bool)
Date of length 0
> 
> 
> 
> 
> cleanEx()
> nameEx("expanding")
> ### * expanding
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: expanding
> ### Title: Expanding Window Functions
> ### Aliases: expanding expanding.mean expanding.sum expanding.product
> ###   expanding.max expanding.min expanding.sd expanding.rank expanding.cor
> ###   expanding.cov
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=rnorm(100))
> 
> x.emax <- expanding.max(x)
> x.emin <- expanding.min(x)
> 
> 
> 
> cleanEx()
> nameEx("fill")
> ### * fill
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fill
> ### Title: Fill Missing Values
> ### Aliases: fill fill.fwd fill.bwd fill.value
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=50),rnorm(50))
> x[x > 0,] <- NA
> fill.fwd(x)
                  [,1]
2022-04-11 -0.62645381
2022-04-12 -0.62645381
2022-04-13 -0.83562861
2022-04-14 -0.83562861
2022-04-15 -0.83562861
2022-04-16 -0.82046838
2022-04-17 -0.82046838
2022-04-18 -0.82046838
2022-04-19 -0.82046838
2022-04-20 -0.30538839
2022-04-21 -0.30538839
2022-04-22 -0.30538839
2022-04-23 -0.62124058
2022-04-24 -2.21469989
2022-04-25 -2.21469989
2022-04-26 -0.04493361
2022-04-27 -0.01619026
2022-04-28 -0.01619026
2022-04-29 -0.01619026
2022-04-30 -0.01619026
2022-05-01 -0.01619026
2022-05-02 -0.01619026
2022-05-03 -0.01619026
2022-05-04 -1.98935170
2022-05-05 -1.98935170
2022-05-06 -0.05612874
2022-05-07 -0.15579551
2022-05-08 -1.47075238
2022-05-09 -0.47815006
2022-05-10 -0.47815006
2022-05-11 -0.47815006
2022-05-12 -0.10278773
2022-05-13 -0.10278773
2022-05-14 -0.05380504
2022-05-15 -1.37705956
2022-05-16 -0.41499456
2022-05-17 -0.39428995
2022-05-18 -0.05931340
2022-05-19 -0.05931340
2022-05-20 -0.05931340
2022-05-21 -0.16452360
2022-05-22 -0.25336168
2022-05-23 -0.25336168
2022-05-24 -0.25336168
2022-05-25 -0.68875569
2022-05-26 -0.70749516
2022-05-27 -0.70749516
2022-05-28 -0.70749516
2022-05-29 -0.11234621
2022-05-30 -0.11234621
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=50),rnorm(50))
> x[x > 0,] <- NA
> fill.bwd(x)
                 [,1]
2022-04-11 -0.6120264
2022-04-12 -0.6120264
2022-04-13 -1.1293631
2022-04-14 -1.1293631
2022-04-15 -0.3672215
2022-04-16 -0.3672215
2022-04-17 -0.3672215
2022-04-18 -1.0441346
2022-04-19 -0.1350546
2022-04-20 -0.1350546
2022-04-21 -0.0392400
2022-04-22 -0.0392400
2022-04-23 -0.7432732
2022-04-24 -0.7432732
2022-04-25 -0.7432732
2022-04-26 -1.8049586
2022-04-27 -1.8049586
2022-04-28 -0.7099464
2022-04-29 -0.7099464
2022-04-30 -0.7099464
2022-05-01 -0.7099464
2022-05-02 -0.7099464
2022-05-03 -0.9340976
2022-05-04 -0.9340976
2022-05-05 -1.2536334
2022-05-06 -0.4432919
2022-05-07 -0.4432919
2022-05-08 -0.5895209
2022-05-09 -0.5895209
2022-05-10 -0.5895209
2022-05-11 -0.5686687
2022-05-12 -0.1351786
2022-05-13 -1.5235668
2022-05-14 -1.5235668
2022-05-15 -0.3041839
2022-05-16 -0.3041839
2022-05-17 -0.3041839
2022-05-18 -0.3041839
2022-05-19 -0.5425200
2022-05-20 -0.5425200
2022-05-21 -0.5425200
2022-05-22 -1.2765922
2022-05-23 -1.2765922
2022-05-24 -1.2765922
2022-05-25 -1.2765922
2022-05-26 -1.2765922
2022-05-27 -1.2765922
2022-05-28 -0.5732654
2022-05-29 -1.2246126
2022-05-30 -0.4734006
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=50),rnorm(50))
> x[x > 0,] <- NA
> fill.value(x,100.0)
                   [,1]
2022-04-11  -0.62036668
2022-04-12 100.00000000
2022-04-13  -0.91092165
2022-04-14 100.00000000
2022-04-15  -0.65458464
2022-04-16 100.00000000
2022-04-17 100.00000000
2022-04-18 100.00000000
2022-04-19 100.00000000
2022-04-20 100.00000000
2022-04-21  -0.63573645
2022-04-22  -0.46164473
2022-04-23 100.00000000
2022-04-24  -0.65069635
2022-04-25  -0.20738074
2022-04-26  -0.39280793
2022-04-27  -0.31999287
2022-04-28  -0.27911330
2022-04-29 100.00000000
2022-04-30  -0.17733048
2022-05-01  -0.50595746
2022-05-02 100.00000000
2022-05-03  -0.21457941
2022-05-04  -0.17955653
2022-05-05  -0.10019074
2022-05-06 100.00000000
2022-05-07  -0.07356440
2022-05-08  -0.03763417
2022-05-09  -0.68166048
2022-05-10  -0.32427027
2022-05-11 100.00000000
2022-05-12  -0.58889449
2022-05-13 100.00000000
2022-05-14  -1.51839408
2022-05-15 100.00000000
2022-05-16  -1.53644982
2022-05-17  -0.30097613
2022-05-18  -0.52827990
2022-05-19  -0.65209478
2022-05-20  -0.05689678
2022-05-21  -1.91435943
2022-05-22 100.00000000
2022-05-23  -1.66497244
2022-05-24  -0.46353040
2022-05-25  -1.11592011
2022-05-26  -0.75081900
2022-05-27 100.00000000
2022-05-28 100.00000000
2022-05-29  -1.28630053
2022-05-30  -1.64060553
> 
> 
> 
> cleanEx()
> nameEx("frequency.convert")
> ### * frequency.convert
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: frequency.convert
> ### Title: Change Frequencies
> ### Aliases: frequency.convert to.weekly to.day.of.week to.monthly
> ###   to.quarterly to.daily to.hourly to.minute to.second to.yearly
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=500),data=1:500)
> 
> to.weekly(x)
           [,1]
2022-04-16    6
2022-04-23   13
2022-04-30   20
2022-05-07   27
2022-05-14   34
2022-05-21   41
2022-05-28   48
2022-06-04   55
2022-06-11   62
2022-06-18   69
2022-06-25   76
2022-07-02   83
2022-07-09   90
2022-07-16   97
2022-07-23  104
2022-07-30  111
2022-08-06  118
2022-08-13  125
2022-08-20  132
2022-08-27  139
2022-09-03  146
2022-09-10  153
2022-09-17  160
2022-09-24  167
2022-10-01  174
2022-10-08  181
2022-10-15  188
2022-10-22  195
2022-10-29  202
2022-11-05  209
2022-11-12  216
2022-11-19  223
2022-11-26  230
2022-12-03  237
2022-12-10  244
2022-12-17  251
2022-12-24  258
2022-12-31  265
2023-01-07  272
2023-01-14  279
2023-01-21  286
2023-01-28  293
2023-02-04  300
2023-02-11  307
2023-02-18  314
2023-02-25  321
2023-03-04  328
2023-03-11  335
2023-03-18  342
2023-03-25  349
2023-04-01  356
2023-04-08  363
2023-04-15  370
2023-04-22  377
2023-04-29  384
2023-05-06  391
2023-05-13  398
2023-05-20  405
2023-05-27  412
2023-06-03  419
2023-06-10  426
2023-06-17  433
2023-06-24  440
2023-07-01  447
2023-07-08  454
2023-07-15  461
2023-07-22  468
2023-07-29  475
2023-08-05  482
2023-08-12  489
2023-08-19  496
2023-08-23  500
> to.monthly(x)
           [,1]
2022-04-30   20
2022-05-31   51
2022-06-30   81
2022-07-31  112
2022-08-31  143
2022-09-30  173
2022-10-31  204
2022-11-30  234
2022-12-31  265
2023-01-31  296
2023-02-28  324
2023-03-31  355
2023-04-30  385
2023-05-31  416
2023-06-30  446
2023-07-31  477
2023-08-23  500
> to.quarterly(x)
           [,1]
2022-06-30   81
2022-09-30  173
2022-12-31  265
2023-03-31  355
2023-06-30  446
2023-08-23  500
> 
> 
> 
> cleanEx()
> nameEx("fts")
> ### * fts
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: fts
> ### Title: Fts: a fast timeseries library
> ### Aliases: fts Ops.fts [.fts [<-.fts cbind.fts rbind.fts print.fts
> ###   plot.fts
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="months",length.out=24),data=1:24)
> y <- fts(index=seq(from=Sys.Date(),by="months",length.out=12),data=13:24)
> xx <- x[1:10,]
> 
> ## intersection of dates is taken for Arith methods
> xyp <- x + y
> xys <- x - y
> xym <- x * y
> xyd <- x / y
> xyg <- x > y
> xyl <- x < y
> 
> cxy <- cbind(x,y)
> rxy <- rbind(x,y)
> print(x)
           [,1]
2022-04-11    1
2022-05-11    2
2022-06-11    3
2022-07-11    4
2022-08-11    5
2022-09-11    6
2022-10-11    7
2022-11-11    8
2022-12-11    9
2023-01-11   10
2023-02-11   11
2023-03-11   12
2023-04-11   13
2023-05-11   14
2023-06-11   15
2023-07-11   16
2023-08-11   17
2023-09-11   18
2023-10-11   19
2023-11-11   20
2023-12-11   21
2024-01-11   22
2024-02-11   23
2024-03-11   24
> plot(x)
> 
> 
> 
> cleanEx()
> nameEx("indicators")
> ### * indicators
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: indicators
> ### Title: Trading indicators
> ### Aliases: indicators above.ma analog below.ma wday mday diff.fts up down
> ###   ema gap.continue gap.direction gap.down gap.down.continue
> ###   gap.down.reverse gap.reverse gap.up gap.up.continue gap.up.reverse
> ###   higher.high higher.low hl.oc.ratio inside.day inside.day.direction
> ###   inside.day.down inside.day.up lower.high lower.low ma.crossover
> ###   ma.crossover.down ma.crossover.up ma.d ma.distance month year
> ###   monthly.sum new.high new.low outside.day outside.day.direction
> ###   outside.day.down outside.day.up pct.chg repeated rsi rsi.crossover
> ###   rsi.crossover.down rsi.crossover.up template.fts trend.day
> ###   trend.day.down trend.day.up
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="months",length.out=5),rnorm(5))
> print(x)
                 [,1]
2022-04-11 -0.6264538
2022-05-11  0.1836433
2022-06-11 -0.8356286
2022-07-11  1.5952808
2022-08-11  0.3295078
> lag(x,1)
                 [,1]
2022-05-11 -0.6264538
2022-06-11  0.1836433
2022-07-11 -0.8356286
2022-08-11  1.5952808
> lead(x,1)
                 [,1]
2022-04-11  0.1836433
2022-05-11 -0.8356286
2022-06-11  1.5952808
2022-07-11  0.3295078
> 
> 
> 
> cleanEx()
> nameEx("intersect.all")
> ### * intersect.all
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: intersect.all
> ### Title: find date intersection among multiple fts objects
> ### Aliases: intersect.all
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
> y <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
> y <- y[1:nrow(y) %% 2==0,]
> intersect.all(x,y)
 [1] "2022-04-12" "2022-04-14" "2022-04-16" "2022-04-18" "2022-04-20"
 [6] "2022-04-22" "2022-04-24" "2022-04-26" "2022-04-28" "2022-04-30"
[11] "2022-05-02" "2022-05-04" "2022-05-06" "2022-05-08" "2022-05-10"
[16] "2022-05-12" "2022-05-14" "2022-05-16" "2022-05-18" "2022-05-20"
[21] "2022-05-22" "2022-05-24" "2022-05-26" "2022-05-28" "2022-05-30"
[26] "2022-06-01" "2022-06-03" "2022-06-05" "2022-06-07" "2022-06-09"
[31] "2022-06-11" "2022-06-13" "2022-06-15" "2022-06-17" "2022-06-19"
[36] "2022-06-21" "2022-06-23" "2022-06-25" "2022-06-27" "2022-06-29"
[41] "2022-07-01" "2022-07-03" "2022-07-05" "2022-07-07" "2022-07-09"
[46] "2022-07-11" "2022-07-13" "2022-07-15" "2022-07-17" "2022-07-19"
> 
> 
> 
> cleanEx()
> nameEx("lead.lag")
> ### * lead.lag
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: lead.lag
> ### Title: Shift an Fts ojbect in time
> ### Aliases: lead.lag.fts lead lag.fts lead.fts
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=10),data=1:10)
> print(x)
           [,1]
2022-04-11    1
2022-04-12    2
2022-04-13    3
2022-04-14    4
2022-04-15    5
2022-04-16    6
2022-04-17    7
2022-04-18    8
2022-04-19    9
2022-04-20   10
> lag(x,1)
           [,1]
2022-04-12    1
2022-04-13    2
2022-04-14    3
2022-04-15    4
2022-04-16    5
2022-04-17    6
2022-04-18    7
2022-04-19    8
2022-04-20    9
> lead(x,1)
           [,1]
2022-04-11    2
2022-04-12    3
2022-04-13    4
2022-04-14    5
2022-04-15    6
2022-04-16    7
2022-04-17    8
2022-04-18    9
2022-04-19   10
> 
> 
> 
> cleanEx()
> nameEx("moving")
> ### * moving
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: moving
> ### Title: Moving Functions
> ### Aliases: moving.functions moving.mean moving.sum moving.product
> ###   moving.max moving.min moving.sd moving.rank moving.cor moving.cov
> ###   cor.by.row
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
> y <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
> 
> x.mean <- moving.mean(x,20)
> x.sum <- moving.sum(x,20)
> x.prod <- moving.product(x,20)
tslib/tslib/vector.summary/prod.hpp:53:6: runtime error: signed integer overflow: 479001600 * 13 cannot be represented in type 'int'
    #0 0x7f3527437cd9 in int tslib::Prod<int>::apply<int*>(int*, int*) tslib/tslib/vector.summary/prod.hpp:53
    #1 0x7f3527437cd9 in void tslib::windowApply<int, tslib::Prod>::apply<int*, int*>(int*, int*, int*, unsigned long) tslib/tslib/utils/window.apply.hpp:36
    #2 0x7f3527437cd9 in tslib::TSeries<double, int, int, JulianBackend, tslib::JulianDate> const tslib::TSeries<double, int, int, JulianBackend, tslib::JulianDate>::window<int, tslib::Prod>(unsigned long) const tslib/tslib/tseries.hpp:314
    #3 0x7f35274386e5 in SEXPREC* windowFun<double, int, int, JulianBackend, tslib::JulianDate, tslib::Prod, tslib::prodTraits>(SEXPREC*, SEXPREC*) helpers/window.template.hpp:28
    #4 0x7f352747a53f in SEXPREC* windowSpecializer<tslib::Prod, tslib::prodTraits>(SEXPREC*, SEXPREC*) helpers/window.template.hpp:43
    #5 0x580b87 in R_doDotCall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:604
    #6 0x589d5c in do_dotcall /data/gannet/ripley/R/svn/R-devel/src/main/dotcode.c:1284
    #7 0x62d766 in bcEval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:7136
    #8 0x675027 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:748
    #9 0x67a100 in R_execClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1918
    #10 0x67c4f7 in Rf_applyClosure /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:1844
    #11 0x67569f in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:871
    #12 0x681779 in do_set /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:2991
    #13 0x675ac0 in Rf_eval /data/gannet/ripley/R/svn/R-devel/src/main/eval.c:823
    #14 0x6f765d in Rf_ReplIteration /data/gannet/ripley/R/svn/R-devel/src/main/main.c:264
    #15 0x6f7cf0 in R_ReplConsole /data/gannet/ripley/R/svn/R-devel/src/main/main.c:316
    #16 0x6f7e34 in run_Rmainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1137
    #17 0x6f7e82 in Rf_mainloop /data/gannet/ripley/R/svn/R-devel/src/main/main.c:1144
    #18 0x41b418 in main /data/gannet/ripley/R/svn/R-devel/src/main/Rmain.c:29
    #19 0x7f35380f4b74 in __libc_start_main (/lib64/libc.so.6+0x27b74)
    #20 0x41dc1d in _start (/data/gannet/ripley/R/gcc-SAN/bin/exec/R+0x41dc1d)

> x.max <- moving.max(x,20)
> x.min <- moving.min(x,20)
> x.sd <- moving.sd(x,20)
> x.rank <- moving.rank(x,20)
> 
> ## take only odd rows
> ## to illustrate that teh correlation and covariance
> ## will only be calculated for the intersection of the dates
> y <- y[(1:nrow(y))%%2 == 1]
> 
> xy.cor <- moving.cor(x, y, 20)
> xy.cov <- moving.cov(x, y, 20)
> 
> 
> 
> cleanEx()
> nameEx("pad.trim")
> ### * pad.trim
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: pad
> ### Title: pad and trim dates
> ### Aliases: pad.trim pad trim filter.min.obs
> ### Keywords: ts
> 
> ### ** Examples
> 
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=5),data=1:5)
> pad.dates <- index(x)[1] + c(10L,20L)
> pad(x,pad.dates)
           [,1]
2022-04-11    1
2022-04-12    2
2022-04-13    3
2022-04-14    4
2022-04-15    5
2022-04-21   NA
2022-05-01   NA
> 
> trim.dts <- index(x)[c(1,3)]
> 
> trim(x,trim.dts)
           [,1]
2022-04-11    1
2022-04-13    3
> 
> 
> 
> cleanEx()
> nameEx("read.write.fts")
> ### * read.write.fts
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: read.write.fts
> ### Title: Read / Write Files
> ### Aliases: read.write.fts read.csv.fts write.csv.fts
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),data=1:100)
> colnames(x) <- "big.ass.black.dog"
> 
> csv.fname <- paste(tempfile(),".csv",sep="")
> write.csv.fts(x,csv.fname)
> y.csv <- read.csv.fts(csv.fname)
> 
> all.equal(x,y.csv)
[1] TRUE
> 
> 
> 
> cleanEx()
> nameEx("remove.rows")
> ### * remove.rows
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: remove.rows
> ### Title: Remove Rows
> ### Aliases: remove.rows remove.na.rows remove.all.na.rows
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=10),matrix(rnorm(20),ncol=2))
> 
> x[5,1] <- NA
> x[10,] <- NA
> 
> print(x)
                 [,1]        [,2]
2022-04-11 -0.6264538  1.51178117
2022-04-12  0.1836433  0.38984324
2022-04-13 -0.8356286 -0.62124058
2022-04-14  1.5952808 -2.21469989
2022-04-15         NA  1.12493092
2022-04-16 -0.8204684 -0.04493361
2022-04-17  0.4874291 -0.01619026
2022-04-18  0.7383247  0.94383621
2022-04-19  0.5757814  0.82122120
2022-04-20         NA          NA
> 
> ## will drop rows where NA's appear
> ## in any of the columns
> remove.na.rows(x)
                 [,1]        [,2]
2022-04-11 -0.6264538  1.51178117
2022-04-12  0.1836433  0.38984324
2022-04-13 -0.8356286 -0.62124058
2022-04-14  1.5952808 -2.21469989
2022-04-16 -0.8204684 -0.04493361
2022-04-17  0.4874291 -0.01619026
2022-04-18  0.7383247  0.94383621
2022-04-19  0.5757814  0.82122120
> 
> ## will drop rows where NA's appear
> ## in all of the columns
> remove.all.na.rows(x)
                 [,1]        [,2]
2022-04-11 -0.6264538  1.51178117
2022-04-12  0.1836433  0.38984324
2022-04-13 -0.8356286 -0.62124058
2022-04-14  1.5952808 -2.21469989
2022-04-15         NA  1.12493092
2022-04-16 -0.8204684 -0.04493361
2022-04-17  0.4874291 -0.01619026
2022-04-18  0.7383247  0.94383621
2022-04-19  0.5757814  0.82122120
> 
> 
> 
> cleanEx()
> nameEx("since.na")
> ### * since.na
> 
> flush(stderr()); flush(stdout())
> 
> ### Name: since.na
> ### Title: Count distance since an NA has occurred
> ### Aliases: since.na
> ### Keywords: ts
> 
> ### ** Examples
> 
> x <- fts(index=seq(from=Sys.Date(),by="days",length.out=100),rnorm(100))
> 
> x[10,] <- NA
> 
> since.na(x)
           [,1]
2022-04-11   -1
2022-04-12   -1
2022-04-13   -1
2022-04-14   -1
2022-04-15   -1
2022-04-16   -1
2022-04-17   -1
2022-04-18   -1
2022-04-19   -1
2022-04-20    0
2022-04-21    1
2022-04-22    2
2022-04-23    3
2022-04-24    4
2022-04-25    5
2022-04-26    6
2022-04-27    7
2022-04-28    8
2022-04-29    9
2022-04-30   10
2022-05-01   11
2022-05-02   12
2022-05-03   13
2022-05-04   14
2022-05-05   15
2022-05-06   16
2022-05-07   17
2022-05-08   18
2022-05-09   19
2022-05-10   20
2022-05-11   21
2022-05-12   22
2022-05-13   23
2022-05-14   24
2022-05-15   25
2022-05-16   26
2022-05-17   27
2022-05-18   28
2022-05-19   29
2022-05-20   30
2022-05-21   31
2022-05-22   32
2022-05-23   33
2022-05-24   34
2022-05-25   35
2022-05-26   36
2022-05-27   37
2022-05-28   38
2022-05-29   39
2022-05-30   40
2022-05-31   41
2022-06-01   42
2022-06-02   43
2022-06-03   44
2022-06-04   45
2022-06-05   46
2022-06-06   47
2022-06-07   48
2022-06-08   49
2022-06-09   50
2022-06-10   51
2022-06-11   52
2022-06-12   53
2022-06-13   54
2022-06-14   55
2022-06-15   56
2022-06-16   57
2022-06-17   58
2022-06-18   59
2022-06-19   60
2022-06-20   61
2022-06-21   62
2022-06-22   63
2022-06-23   64
2022-06-24   65
2022-06-25   66
2022-06-26   67
2022-06-27   68
2022-06-28   69
2022-06-29   70
2022-06-30   71
2022-07-01   72
2022-07-02   73
2022-07-03   74
2022-07-04   75
2022-07-05   76
2022-07-06   77
2022-07-07   78
2022-07-08   79
2022-07-09   80
2022-07-10   81
2022-07-11   82
2022-07-12   83
2022-07-13   84
2022-07-14   85
2022-07-15   86
2022-07-16   87
2022-07-17   88
2022-07-18   89
2022-07-19   90
> 
> 
> 
> ### * <FOOTER>
> ###
> cleanEx()
> options(digits = 7L)
> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
Time elapsed:  1.194 0.142 1.758 0 0 
> grDevices::dev.off()
null device 
          1 
> ###
> ### Local variables: ***
> ### mode: outline-minor ***
> ### outline-regexp: "\\(> \\)?### [*]+" ***
> ### End: ***
> quit('no')