README.md
In alberto-mateos-mo/tsextras: Provides Additional Funtions to Analise Time Series
tsextras
The goal of tsextras is to provide helper functions to analyse time
series objects.
Installation
You can install the development version from
GitHub with:
# install.packages("devtools")
devtools::install_github("alberto-mateos-mo/tsextras")
Example
ts_plot() function is a wrapper for other functions that plot ts
objects.
library(tsextras)
library(ggplot2)
ts_plot(AirPassengers)
ts_trend() extracts and plots the trend of a time series.
library(tsextras)
library(ggplot2)
ts_trend(AirPassengers, order = 12)
#> Registered S3 method overwritten by 'xts':
#> method from
#> as.zoo.xts zoo
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> Registered S3 methods overwritten by 'forecast':
#> method from
#> fitted.fracdiff fracdiff
#> residuals.fracdiff fracdiff
#> $trend.series
#> Jan Feb Mar Apr May Jun Jul Aug
#> 1949 NA NA NA NA NA NA 126.7917 127.2500
#> 1950 131.2500 133.0833 134.9167 136.4167 137.4167 138.7500 140.9167 143.1667
#> 1951 157.1250 159.5417 161.8333 164.1250 166.6667 169.0833 171.2500 173.5833
#> 1952 183.1250 186.2083 189.0417 191.2917 193.5833 195.8333 198.0417 199.7500
#> 1953 215.8333 218.5000 220.9167 222.9167 224.0833 224.7083 225.3333 225.3333
#> 1954 228.0000 230.4583 232.2500 233.9167 235.6250 237.7500 240.5000 243.9583
#> 1955 261.8333 266.6667 271.1250 275.2083 278.5000 281.9583 285.7500 289.3333
#> 1956 309.9583 314.4167 318.6250 321.7500 324.5000 327.0833 329.5417 331.8333
#> 1957 348.2500 353.0000 357.6250 361.3750 364.5000 367.1667 369.4583 371.2083
#> 1958 375.2500 377.9167 379.5000 380.0000 380.7083 380.9583 381.8333 383.6667
#> 1959 402.5417 407.1667 411.8750 416.3333 420.5000 425.5000 430.7083 435.1250
#> 1960 456.3333 461.3750 465.2083 469.3333 472.7500 475.0417 NA NA
#> Sep Oct Nov Dec
#> 1949 127.9583 128.5833 129.0000 129.7500
#> 1950 145.7083 148.4167 151.5417 154.7083
#> 1951 175.4583 176.8333 178.0417 180.1667
#> 1952 202.2083 206.2500 210.4167 213.3750
#> 1953 224.9583 224.5833 224.4583 225.5417
#> 1954 247.1667 250.2500 253.5000 257.1250
#> 1955 293.2500 297.1667 301.0000 305.4583
#> 1956 334.4583 337.5417 340.5417 344.0833
#> 1957 372.1667 372.4167 372.7500 373.6250
#> 1958 386.5000 390.3333 394.7083 398.6250
#> 1959 437.7083 440.9583 445.8333 450.6250
#> 1960 NA NA NA NA
#>
#> $trend.plot
#> Warning: Removed 12 rows containing missing values (geom_path).
#>
#> $detrended.series
#> Jan Feb Mar Apr May Jun
#> 1949 NA NA NA NA NA NA
#> 1950 -16.250000 -7.083333 6.083333 -1.416667 -12.416667 10.250000
#> 1951 -12.125000 -9.541667 16.166667 -1.125000 5.333333 8.916667
#> 1952 -12.125000 -6.208333 3.958333 -10.291667 -10.583333 22.166667
#> 1953 -19.833333 -22.500000 15.083333 12.083333 4.916667 18.291667
#> 1954 -24.000000 -42.458333 2.750000 -6.916667 -1.625000 26.250000
#> 1955 -19.833333 -33.666667 -4.125000 -6.208333 -8.500000 33.041667
#> 1956 -25.958333 -37.416667 -1.625000 -8.750000 -6.500000 46.916667
#> 1957 -33.250000 -52.000000 -1.625000 -13.375000 -9.500000 54.833333
#> 1958 -35.250000 -59.916667 -17.500000 -32.000000 -17.708333 54.041667
#> 1959 -42.541667 -65.166667 -5.875000 -20.333333 -0.500000 46.500000
#> 1960 -39.333333 -70.375000 -46.208333 -8.333333 -0.750000 59.958333
#> Jul Aug Sep Oct Nov Dec
#> 1949 21.208333 20.750000 8.041667 -9.583333 -25.000000 -11.750000
#> 1950 29.083333 26.833333 12.291667 -15.416667 -37.541667 -14.708333
#> 1951 27.750000 25.416667 8.541667 -14.833333 -32.041667 -14.166667
#> 1952 31.958333 42.250000 6.791667 -15.250000 -38.416667 -19.375000
#> 1953 38.666667 46.666667 12.041667 -13.583333 -44.458333 -24.541667
#> 1954 61.500000 49.041667 11.833333 -21.250000 -50.500000 -28.125000
#> 1955 78.250000 57.666667 18.750000 -23.166667 -64.000000 -27.458333
#> 1956 83.458333 73.166667 20.541667 -31.541667 -69.541667 -38.083333
#> 1957 95.541667 95.791667 31.833333 -25.416667 -67.750000 -37.625000
#> 1958 109.166667 121.333333 17.500000 -31.333333 -84.708333 -61.625000
#> 1959 117.291667 123.875000 25.291667 -33.958333 -83.833333 -45.625000
#> 1960 NA NA NA NA NA NA
#>
#> $order.f
#> [1] 12
ts_season() extracts and plots seasonal component of a time series.
library(tsextras)
library(ggplot2)
s <- AirPassengers
x <- ts_trend(s)
ts_season(x)
#> Warning in matrix(data = x$detrended.series, nrow = x$order): data length [144]
#> is not a sub-multiple or multiple of the number of rows [5]
#> $season.series
#> [1] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [7] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [13] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [19] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [25] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [31] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [37] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [43] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [49] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [55] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [61] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [67] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [73] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [79] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [85] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [91] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [97] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [103] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [109] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [115] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [121] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [127] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [133] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [139] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#>
#> $season.plot
#>
#> $random.series
#> Jan Feb Mar Apr May
#> 1949 NA NA 7.25714286 -0.15714286 -10.74285714
#> 1950 -8.14285714 -3.15714286 13.85714286 -0.02857143 -17.80714286
#> 1951 0.85714286 -5.02857143 17.59285714 -7.54285714 -8.15714286
#> 1952 0.99285714 -0.54285714 9.24285714 -8.74285714 -17.82857143
#> 1953 -4.95714286 -14.14285714 17.77142857 8.39285714 -14.74285714
#> 1954 2.57142857 -21.80714286 15.05714286 -4.75714286 -17.14285714
#> 1955 4.85714286 -17.15714286 12.05714286 -1.62857143 -25.80714286
#> 1956 6.65714286 -16.62857143 16.39285714 -9.14285714 -31.15714286
#> 1957 6.39285714 -26.54285714 18.84285714 -7.14285714 -34.02857143
#> 1958 5.64285714 -21.54285714 15.97142857 -16.00714286 -39.14285714
#> 1959 9.17142857 -25.00714286 18.85714286 -13.35714286 -27.14285714
#> 1960 15.85714286 -29.75714286 -11.74285714 5.57142857 -28.60714286
#> Jun Jul Aug Sep Oct
#> 1949 -1.02857143 11.59285714 8.45714286 2.84285714 -4.74285714
#> 1950 -3.14285714 13.44285714 15.25714286 9.17142857 -8.80714286
#> 1951 -2.94285714 12.77142857 15.79285714 3.65714286 -11.55714286
#> 1952 8.39285714 11.25714286 21.84285714 1.45714286 -10.42857143
#> 1953 -7.75714286 16.25714286 26.77142857 5.39285714 -11.54285714
#> 1954 0.17142857 32.79285714 21.25714286 -0.35714286 -12.34285714
#> 1955 -0.34285714 40.24285714 25.85714286 5.37142857 -14.40714286
#> 1956 10.65714286 40.17142857 35.59285714 2.65714286 -24.75714286
#> 1957 11.79285714 40.05714286 43.84285714 7.65714286 -24.62857143
#> 1958 4.44285714 52.65714286 66.37142857 -8.60714286 -26.34285714
#> 1959 -6.82857143 56.79285714 66.85714286 -6.95714286 -30.94285714
#> 1960 -6.54285714 71.24285714 60.85714286 -9.22857143 -17.20714286
#> Nov Dec
#> 1949 -14.22857143 2.79285714
#> 1950 -26.34285714 1.44285714
#> 1951 -18.54285714 1.17142857
#> 1952 -19.20714286 1.85714286
#> 1953 -28.75714286 5.45714286
#> 1954 -29.22857143 2.99285714
#> 1955 -42.34285714 5.84285714
#> 1956 -38.34285714 6.37142857
#> 1957 -40.20714286 4.45714286
#> 1958 -46.15714286 -3.34285714
#> 1959 -48.62857143 9.79285714
#> 1960 NA NA
alberto-mateos-mo/tsextras documentation built on Feb. 3, 2020, 12:03 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
tsextras
The goal of tsextras is to provide helper functions to analyse time series objects.
Installation
You can install the development version from GitHub with:
# install.packages("devtools")
devtools::install_github("alberto-mateos-mo/tsextras")
Example
ts_plot() function is a wrapper for other functions that plot ts
objects.
library(tsextras)
library(ggplot2)
ts_plot(AirPassengers)
ts_trend() extracts and plots the trend of a time series.
library(tsextras)
library(ggplot2)
ts_trend(AirPassengers, order = 12)
#> Registered S3 method overwritten by 'xts':
#> method from
#> as.zoo.xts zoo
#> Registered S3 method overwritten by 'quantmod':
#> method from
#> as.zoo.data.frame zoo
#> Registered S3 methods overwritten by 'forecast':
#> method from
#> fitted.fracdiff fracdiff
#> residuals.fracdiff fracdiff
#> $trend.series
#> Jan Feb Mar Apr May Jun Jul Aug
#> 1949 NA NA NA NA NA NA 126.7917 127.2500
#> 1950 131.2500 133.0833 134.9167 136.4167 137.4167 138.7500 140.9167 143.1667
#> 1951 157.1250 159.5417 161.8333 164.1250 166.6667 169.0833 171.2500 173.5833
#> 1952 183.1250 186.2083 189.0417 191.2917 193.5833 195.8333 198.0417 199.7500
#> 1953 215.8333 218.5000 220.9167 222.9167 224.0833 224.7083 225.3333 225.3333
#> 1954 228.0000 230.4583 232.2500 233.9167 235.6250 237.7500 240.5000 243.9583
#> 1955 261.8333 266.6667 271.1250 275.2083 278.5000 281.9583 285.7500 289.3333
#> 1956 309.9583 314.4167 318.6250 321.7500 324.5000 327.0833 329.5417 331.8333
#> 1957 348.2500 353.0000 357.6250 361.3750 364.5000 367.1667 369.4583 371.2083
#> 1958 375.2500 377.9167 379.5000 380.0000 380.7083 380.9583 381.8333 383.6667
#> 1959 402.5417 407.1667 411.8750 416.3333 420.5000 425.5000 430.7083 435.1250
#> 1960 456.3333 461.3750 465.2083 469.3333 472.7500 475.0417 NA NA
#> Sep Oct Nov Dec
#> 1949 127.9583 128.5833 129.0000 129.7500
#> 1950 145.7083 148.4167 151.5417 154.7083
#> 1951 175.4583 176.8333 178.0417 180.1667
#> 1952 202.2083 206.2500 210.4167 213.3750
#> 1953 224.9583 224.5833 224.4583 225.5417
#> 1954 247.1667 250.2500 253.5000 257.1250
#> 1955 293.2500 297.1667 301.0000 305.4583
#> 1956 334.4583 337.5417 340.5417 344.0833
#> 1957 372.1667 372.4167 372.7500 373.6250
#> 1958 386.5000 390.3333 394.7083 398.6250
#> 1959 437.7083 440.9583 445.8333 450.6250
#> 1960 NA NA NA NA
#>
#> $trend.plot
#> Warning: Removed 12 rows containing missing values (geom_path).
#>
#> $detrended.series
#> Jan Feb Mar Apr May Jun
#> 1949 NA NA NA NA NA NA
#> 1950 -16.250000 -7.083333 6.083333 -1.416667 -12.416667 10.250000
#> 1951 -12.125000 -9.541667 16.166667 -1.125000 5.333333 8.916667
#> 1952 -12.125000 -6.208333 3.958333 -10.291667 -10.583333 22.166667
#> 1953 -19.833333 -22.500000 15.083333 12.083333 4.916667 18.291667
#> 1954 -24.000000 -42.458333 2.750000 -6.916667 -1.625000 26.250000
#> 1955 -19.833333 -33.666667 -4.125000 -6.208333 -8.500000 33.041667
#> 1956 -25.958333 -37.416667 -1.625000 -8.750000 -6.500000 46.916667
#> 1957 -33.250000 -52.000000 -1.625000 -13.375000 -9.500000 54.833333
#> 1958 -35.250000 -59.916667 -17.500000 -32.000000 -17.708333 54.041667
#> 1959 -42.541667 -65.166667 -5.875000 -20.333333 -0.500000 46.500000
#> 1960 -39.333333 -70.375000 -46.208333 -8.333333 -0.750000 59.958333
#> Jul Aug Sep Oct Nov Dec
#> 1949 21.208333 20.750000 8.041667 -9.583333 -25.000000 -11.750000
#> 1950 29.083333 26.833333 12.291667 -15.416667 -37.541667 -14.708333
#> 1951 27.750000 25.416667 8.541667 -14.833333 -32.041667 -14.166667
#> 1952 31.958333 42.250000 6.791667 -15.250000 -38.416667 -19.375000
#> 1953 38.666667 46.666667 12.041667 -13.583333 -44.458333 -24.541667
#> 1954 61.500000 49.041667 11.833333 -21.250000 -50.500000 -28.125000
#> 1955 78.250000 57.666667 18.750000 -23.166667 -64.000000 -27.458333
#> 1956 83.458333 73.166667 20.541667 -31.541667 -69.541667 -38.083333
#> 1957 95.541667 95.791667 31.833333 -25.416667 -67.750000 -37.625000
#> 1958 109.166667 121.333333 17.500000 -31.333333 -84.708333 -61.625000
#> 1959 117.291667 123.875000 25.291667 -33.958333 -83.833333 -45.625000
#> 1960 NA NA NA NA NA NA
#>
#> $order.f
#> [1] 12
ts_season() extracts and plots seasonal component of a time series.
library(tsextras)
library(ggplot2)
s <- AirPassengers
x <- ts_trend(s)
ts_season(x)
#> Warning in matrix(data = x$detrended.series, nrow = x$order): data length [144]
#> is not a sub-multiple or multiple of the number of rows [5]
#> $season.series
#> [1] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [7] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [13] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [19] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [25] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [31] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [37] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [43] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [49] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [55] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [61] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [67] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [73] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [79] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [85] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [91] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [97] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [103] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [109] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#> [115] -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429
#> [121] -0.1714286 -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286
#> [127] -1.1928571 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571
#> [133] 2.3428571 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571
#> [139] 2.1571429 -1.2571429 -0.1714286 -1.1928571 2.3428571 2.1571429
#>
#> $season.plot
#>
#> $random.series
#> Jan Feb Mar Apr May
#> 1949 NA NA 7.25714286 -0.15714286 -10.74285714
#> 1950 -8.14285714 -3.15714286 13.85714286 -0.02857143 -17.80714286
#> 1951 0.85714286 -5.02857143 17.59285714 -7.54285714 -8.15714286
#> 1952 0.99285714 -0.54285714 9.24285714 -8.74285714 -17.82857143
#> 1953 -4.95714286 -14.14285714 17.77142857 8.39285714 -14.74285714
#> 1954 2.57142857 -21.80714286 15.05714286 -4.75714286 -17.14285714
#> 1955 4.85714286 -17.15714286 12.05714286 -1.62857143 -25.80714286
#> 1956 6.65714286 -16.62857143 16.39285714 -9.14285714 -31.15714286
#> 1957 6.39285714 -26.54285714 18.84285714 -7.14285714 -34.02857143
#> 1958 5.64285714 -21.54285714 15.97142857 -16.00714286 -39.14285714
#> 1959 9.17142857 -25.00714286 18.85714286 -13.35714286 -27.14285714
#> 1960 15.85714286 -29.75714286 -11.74285714 5.57142857 -28.60714286
#> Jun Jul Aug Sep Oct
#> 1949 -1.02857143 11.59285714 8.45714286 2.84285714 -4.74285714
#> 1950 -3.14285714 13.44285714 15.25714286 9.17142857 -8.80714286
#> 1951 -2.94285714 12.77142857 15.79285714 3.65714286 -11.55714286
#> 1952 8.39285714 11.25714286 21.84285714 1.45714286 -10.42857143
#> 1953 -7.75714286 16.25714286 26.77142857 5.39285714 -11.54285714
#> 1954 0.17142857 32.79285714 21.25714286 -0.35714286 -12.34285714
#> 1955 -0.34285714 40.24285714 25.85714286 5.37142857 -14.40714286
#> 1956 10.65714286 40.17142857 35.59285714 2.65714286 -24.75714286
#> 1957 11.79285714 40.05714286 43.84285714 7.65714286 -24.62857143
#> 1958 4.44285714 52.65714286 66.37142857 -8.60714286 -26.34285714
#> 1959 -6.82857143 56.79285714 66.85714286 -6.95714286 -30.94285714
#> 1960 -6.54285714 71.24285714 60.85714286 -9.22857143 -17.20714286
#> Nov Dec
#> 1949 -14.22857143 2.79285714
#> 1950 -26.34285714 1.44285714
#> 1951 -18.54285714 1.17142857
#> 1952 -19.20714286 1.85714286
#> 1953 -28.75714286 5.45714286
#> 1954 -29.22857143 2.99285714
#> 1955 -42.34285714 5.84285714
#> 1956 -38.34285714 6.37142857
#> 1957 -40.20714286 4.45714286
#> 1958 -46.15714286 -3.34285714
#> 1959 -48.62857143 9.79285714
#> 1960 NA NA
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