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Summary Statistics of Time-Series

Source: R/basic_stats.R
series_describe.Rd

This function is designed for exploratory purposes.

Usage

series_describe(.invariant, .digits = 4)

Arguments

.invariant

An univariate or multivariate time-series.

.digits

The number of digits to print.

Value

A tibble with basic statistics for exploratory analysis.

See also

skewness, kurtosis

Examples

# univariate
series_describe(diff(log(EuStockMarkets[ , 1, drop = FALSE])))
#> # A tibble: 1 × 13
#>   asset observations    na minimum quartile_1  median    mean quartile_3 maximum
#>   <chr>        <dbl> <dbl>   <dbl>      <dbl>   <dbl>   <dbl>      <dbl>   <dbl>
#> 1 DAX           1859     0 -0.0963   -0.00469 4.73e-4 6.52e-4    0.00636  0.0508
#> # ℹ 4 more variables: variance <dbl>, std <dbl>, skewness <dbl>, kurtosis <dbl>

# multivariate
series_describe(diff(log(EuStockMarkets)))
#> # A tibble: 4 × 13
#>   asset observations    na minimum quartile_1  median    mean quartile_3 maximum
#>   <chr>        <dbl> <dbl>   <dbl>      <dbl>   <dbl>   <dbl>      <dbl>   <dbl>
#> 1 DAX           1859     0 -0.0963   -0.00469 4.73e-4 6.52e-4    0.00636  0.0508
#> 2 SMI           1859     0 -0.0838   -0.00380 8.86e-4 8.18e-4    0.00607  0.0497
#> 3 CAC           1859     0 -0.0758   -0.00606 0       4.37e-4    0.00710  0.0610
#> 4 FTSE          1859     0 -0.0414   -0.00432 8.02e-5 4.32e-4    0.00525  0.0544
#> # ℹ 4 more variables: variance <dbl>, std <dbl>, skewness <dbl>, kurtosis <dbl>