Ratio of lagged observations.

Computes the ratio of lagged observations in a vector.

Usage

lagratio(
  x,
  lag = 1L,
  recursion = 1L,
  differences = recursion,
  direction = c("backward", "forward"),
  ...
)

Arguments

x: A numeric vector or matrix.
lag: An integer representing the lag ‘distance’.
recursion: An integer that indicates the level of recursion for the calculations. A 1 will simply compute the ratios. A 2, for example, will compute the ratios, save the result, and then compute the ratios of the results using the same lag. See examples.
differences: Same as recursion. Used for symmetry with diff.
direction: A string that indicates the direction of calculation. A "backward" indicates that ‘latter’ values are divided by ‘former’ values. A "forward" indicates that ‘former’ values are divided by ‘latter’ values. See examples.
...: Additional arguments to diff().

Value

A vector or matrix of lagged ratios.

Details

This function behaves similarly to diff() except that it returns a vector or matrix of ratios rather than differences.

Author

Derek H. Ogle, DerekOgle51@gmail.com

Examples

## Backward lagged ratios
# no recursion
lagratio(1:10,1)
#> [1] 2.000000 1.500000 1.333333 1.250000 1.200000 1.166667 1.142857 1.125000
#> [9] 1.111111
lagratio(1:10,2)
#> [1] 3.000000 2.000000 1.666667 1.500000 1.400000 1.333333 1.285714 1.250000
# with recursion
lagratio(1:10,1,2)
#> [1] 0.7500000 0.8888889 0.9375000 0.9600000 0.9722222 0.9795918 0.9843750
#> [8] 0.9876543
lagratio(1:10,2,2)
#> [1] 0.5555556 0.7500000 0.8400000 0.8888889 0.9183673 0.9375000

## Forward lagged ratios
# no recursion
lagratio(10:1,1,direction="forward")
#> [1] 1.111111 1.125000 1.142857 1.166667 1.200000 1.250000 1.333333 1.500000
#> [9] 2.000000
lagratio(10:1,2,direction="forward")
#> [1] 1.250000 1.285714 1.333333 1.400000 1.500000 1.666667 2.000000 3.000000
# with recursion
lagratio(10:1,1,2,direction="forward")
#> [1] 0.9876543 0.9843750 0.9795918 0.9722222 0.9600000 0.9375000 0.8888889
#> [8] 0.7500000
lagratio(10:1,2,2,direction="forward")
#> [1] 0.9375000 0.9183673 0.8888889 0.8400000 0.7500000 0.5555556